Вакансии

Location: Remote (USA) Workplace: remote Arcadia is the most trusted healthcare platform powering outcomes. We transform complex healthcare data into trusted intelligence, helping providers, payers, and life sciences organizations act with clarity, make confident decisions, and achieve measurable clinical, operational, and financial outcomes.  Built on a comprehensive data foundation spanning tens of millions of patient lives, Arcadia combines advanced analytics and responsible AI to surface meaningful insights, coordinate action, and improve performance at scale. Our approach to AI and automation is governed and transparent — designed to strengthen human expertise, not replace judgment or obscure responsibility.  Hundreds of organizations rely on Arcadia to improve cost, quality, and outcomes. Backed by Nordic Capital, we continue to invest in our platform, AI capabilities, and people as we pursue our purpose: helping healthcare deliver better outcomes for every person, every community, and every generation.    Why This Role Is Important to Arcadia Arcadia’s data and analytics platform is used by hundreds of health systems, ACOs, payers, and life sciences organizations, touching tens of millions of patient lives. This role owns how our agentic capabilities perform at that same scale: accurate, transparent about their own confidence, and safe for the clinicians, care teams, and patients who depend on them.  As a staff-level individual contributor, you will own the product-layer decisions that shape agent behavior, including prompting, retrieval and context, memory and state, evaluation, and escalation, while partnering with Product and Engineering on the systems that support them. Your work will help Arcadia make evidence-based launch decisions and scale responsible AI that is steerable, trustworthy, and ready for real healthcare workflows.    What Success Looks Like In 3 months You have established a production-grounded baseline for priority agentic workflows, with documented failure modes, severity-weighted evaluation rubrics, and a clear measurement plan You have mapped the current retrieval, context, memory, and escalation patterns and identified the highest-value opportunities to improve reliability, calibration, and cost You have earned trust across Product and Engineering by turning production evidence into clear, actionable recommendations In 6 months What You'll Be Doing Design and iterate on agent behavior across real, live workflows, including long- horizon , multi-turn agentic tasks Design retrieval and context architecture so the right source data reaches a model in the right structure and agents remain grounded in real data rather than filling gaps with assumptions Design memory and state handling across multi-turn and multi-agent flows, determining what is carried forward, summarized, or dropped and why Create context and prompt templates that combine few-shot examples, structured formatting, and reasoning scaffolding for consistent agent behavior Improve performance through prompting, tool-use strategy, and context construction, validated through direct experimentation rather than guesswork Build and run evaluations against real production conditions to measure performance, regressions , failure modes, and edge cases Author evaluation rubrics, quality heuristics, and thresholds that weight failures by severity and cost , not just frequency , and monitor those measures against production behavior Design and validate escalation paths that route agents to human review based on confidence and uncertainty while preserving safety and consistency under adversarial and edge-case conditions Design for cost-aware performance alongside latency, reliability, and accuracy through efficient context construction and tool-call economy Evaluate and sign off on model changes by baselining current behavior, running comparative evaluations, and making the go/no-go call before a change reaches a customer Maintain product-level AI documentation, including model cards, intended use, limitations, and known failure modes, so customer-facing teams work from actual agent behavior Partner closely with Product and product managers to ensure agents are not just capable, but steerable, trustworthy, and ready to scale What You'll Bring Bachelors degree in Engineering or related field and/or masters of Data Science or related field 4+ years of production software engineering experience, including 3+ years of hands-on ownership of ML, LLM, or agentic systems in production, with direct experience in healthcare, finance, or another regulated industry Demonstrated ability to diagnose why an agent failed, correctly attribute the fix to instruction, retrieval, context, or memory design, and weigh failures by severity and cost rather than frequency alone Hands-on experience with RAG architecture, production-grounded evaluation frameworks, and fallback or human-in-the-loop logic for automated systems Working familiarity with AWS AI/ML services, including Bedrock and SageMaker, sufficient to build and evaluate effectively in Arcadia’s environment Evidence-led judgment and the credibility to push back on launch decisions, paired with a builder’s instinct to run the experiment and move from a production failure to a fix Would Love for You to Have Experience applying AI to healthcare data or workflows where safety, transparency, and calibrated uncertainty directly affect care teams or patients Experience with long-horizon, multi-turn or multi-agent workflows and product-level AI documentation such as model cards What You'll Get The opportunity to define how agent performance, safety, and readiness are measured for production healthcare workflows Meaningful ownership across prompts, context, memory, evaluations, and escalation patterns at product scale A cross-functional role translating production evidence into AI improvements used across Arcadia’s platform A mission-driven company working to improve how patients receive care A flexible, remote-friendly culture with personality and heart Employee-driven programs and initiatives for personal and professional development Membership in the talented, energized, diverse, and purpose-driven Arcadian community About Arcadia Arcadia.io helps innovative providers and payers across the country transform healthcare to reduce cost while improving patient health. We do this by aggregating large amounts of disparate data, applying algorithms to identify opportunities to provide better patient care, and making those opportunities actionable by physicians at the point of care in near-real time. We are passionate about helping our customers drive meaningful outcomes. We are growing fast and have emerged as a market leader in the highly competitive population health management software market and have been recognized by industry analysts KLAS, IDC, Forrester, and Chilmark for our leadership. For a better sense of our brand and products, please explore our website. Protect Yourself If you have concerns about the authenticity of a job offer or recruitment-related communication claiming to be from Arcadia, we encourage you to verify by contacting us directly at (781) 202-3600 and select option 3. For more information, visit our website. This position is responsible for following all Security policies and procedures in order to protect all PHI under Arcadia's custodianship as well as Arcadia Intellectual Properties.  For any security-specific roles, the responsibilities would be further defined by the hiring manager.

Location: United States, Aliso Viejo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Senior Software Engineer – Applied AI & Streaming Aliso Viejo, CA The vision We think AI will change what cloud gaming can be. It can make streamed play faster, more personal, and more accessible, and in some ways better than playing locally. As a Senior Software Engineer on our team, you'll build agents and inference-backed systems into a real-time streaming platform and ship them to players. You'll work where AI meets performance-sensitive systems, and a lot of the problems here are still being defined. What you'll do Design, prototype, and ship AI-powered capabilities across our streaming platform and player experience. Apply inference and agents to real-time performance, player engagement, personalization, and accessibility. Use AI to understand, optimize, and evolve large existing codebases, including our streaming stack. Build and extend our platform in C++, and help shape the technologies and architecture we use next. Build what production AI needs: evaluation, telemetry, guardrails, fallbacks, and attention to latency and cost. Turn ambiguous ideas into demos and experiments, measure what works, and harden it for production. Work AI-natively every day, using coding agents, automation, and rapid exploration, and help the team do the same. Work with a small, focused engineering team and with partners across streaming, platform, and cloud. You're a great fit if you have A BS in Computer Science or a related field, or equivalent practical experience. Senior-level software engineering experience with a track record of owning complex systems end to end. Strong C++ skills from professional work in production codebases. Hands-on experience building and deploying agents or AI-powered features in production. You've worked through evals, regressions, latency, cost, and the ways these systems fail. A strong grasp of how to turn models into products, including context and prompt design, tool use and orchestration, memory and retrieval, model selection, and where inference should run. Fluency with AI-native engineering workflows. Product judgment. You can tell when AI makes an experience better and when it's a gimmick. The ability to work in ambiguity, move quickly, and keep momentum as priorities change. Clear communication, strong ownership, and a habit of making the people around you better. Bonus XP Python, Rust, or other languages used to build and serve AI systems. Low-latency or on-device inference, model optimization, or GPU experience. Real-time media, game streaming, graphics, or video experience. Cloud infrastructure, distributed systems, or production platform experience. Experience building conversational or agentic experiences for games or interactive products. Linux or Windows systems experience. Japanese language or cross-cultural collaboration experience. You enjoy playing video games. Why join us Work on AI problems most engineers never get to. In real-time systems, every millisecond counts, and so does every inference call. Help set the direction. Our AI strategy is still taking shape, and you'll help decide what we build, not just how. Get real ownership. You'll join a small, senior team where ideas go from prototype to production quickly. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $177,300 — $265,900 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: Paris, France About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. À propos du poste En tant qu'ingénieur·e en IA appliquée au sein de notre équipe Entreprise, votre rôle est de guider certaines des plus grandes entreprises de France vers la frontière de l'IA et de les aider à déployer Claude dans leurs opérations, leurs produits et leurs méthodes de travail. Vous deviendrez le·la spécialiste incontournable de la plateforme Claude et le·la conseiller·ère technique de confiance de vos clients, en conseillant leurs équipes d'ingénierie sur l'architecture, la conception d'agents et l'évaluation, et en travaillant avec les dirigeants et les cadres supérieurs qui sponsorisent ces programmes pour démontrer la valeur ajoutée de Claude et les aider à prendre une décision éclairée quant à l'adoption de Claude. Les transactions avec les entreprises sont différentes. Les cycles d'approvisionnement sont plus longs, davantage de parties prenantes sont impliquées, et la réussite dépend de la capacité à relier le travail technique aux résultats qui importent pour le conseil d'administration. Vous serez tout aussi à l'aise pour conseiller une équipe d'ingénierie sur l'évaluation et l'architecture que pour présenter un dossier de valeur à un CIO ou un CTO, et vous porterez le fil technique à travers chaque étape d'un engagement s'étalant sur plusieurs trimestres. Une grande partie de ce travail se déroule en français, avec des cadres dirigeants et des équipes d'ingénierie françaises, c'est pourquoi un français natif ou courant est essentiel pour ce poste. Vous travaillerez en étroite collaboration avec les responsables de comptes Entreprise et les architectes IA appliquée pour accompagner chaque client depuis la première conversation, à travers l'évaluation technique, la création de valeur et les achats, jusqu'à la décision de développer sur Claude. Une fois leur décision prise, vous préparerez leur partenaire d'intégration système à assurer la mise en œuvre, en définissant ensemble l'architecture cible et les critères de réussite, et vous resterez proche du client en tant que conseiller·ère technique sur Claude pendant tout le déploiement, tandis que le partenaire se chargera de la construction. En travaillant aux côtés des équipes Produit et Ingénierie d'Anthropic, vous mettrez à profit votre connaissance de la plateforme Claude pour conseiller sur l'évaluation, recommander des architectures répondant aux exigences de sécurité et d'échelle des entreprises, et créer les ressources techniques et commerciales qui aident les grandes organisations à réussir avec Claude. Responsabilités Travailler en partenariat avec les responsables de comptes et les architectes en IA appliquée pour accompagner les clients entreprises en France depuis le premier échange jusqu'à la décision d'adopter Claude, en passant par l'évaluation technique, la validation de la valeur et le processus d'achat Piloter le volet technique de chaque opportunité jusqu'à cette décision, et rester le·la conseiller·ère technique du client sur Claude pendant son déploiement Préparer les clients et leurs partenaires d'intégration de systèmes à assurer la livraison : convenir de l'architecture cible, définir les critères de réussite, et rester disponible pour conseiller l'équipe de livraison au fur et à mesure de l'avancement de la construction Guider les clients grandes entreprises vers l'avant-garde de l'IA, en les conseillant sur la manière de déployer Claude dans leurs opérations, leurs produits et leurs méthodes de travail Aider les équipes d'ingénierie des clients à voir comment elles pourraient développer sur Claude, en couvrant l'architecture, la conception d'agents et l'évaluation, afin qu'elles puissent prendre une décision en toute confiance Élaborer et présenter le dossier de valeur commerciale de Claude auprès des dirigeants et des cadres supérieurs, en français et en anglais, en associant les capacités techniques à des résultats mesurables tels que les coûts, les revenus, les risques et le délai de mise sur le marché Guider les clients à travers de longs cycles d'approvisionnement et d'adoption impliquant de multiples parties prenantes, notamment les évaluations techniques, les preuves de concept, les revues de sécurité et d'architecture, jusqu'à la définition d'une feuille de route claire vers la mise en production Travailler avec les responsables de comptes sur la stratégie de compte, la qualification des opportunités commerciales et les plans d'engagement des dirigeants, et avec les architectes en IA appliquée pour assurer la continuité et le partage du contexte à travers chaque engagement Organiser des briefings exécutifs, des ateliers techniques et des sessions de formation destinés à la fois aux dirigeants et aux équipes d'ingénierie Naviguer au sein des exigences de l'entreprise en matière de sécurité, de conformité, de résidence des données et de gouvernance, en collaborant avec les équipes internes d'Anthropic si nécessaire Identifier les modèles à travers les engagements auprès des entreprises et transmettre les informations aux équipes Produit, Ingénierie et à l'équipe IA appliquée élargie Se rendre sur les sites des clients en France pour des réunions de direction, des ateliers et l'établissement de relations Vous conviendrez particulièrement si vous avez Le français comme langue maternelle ou courant, écrit et parlé, car vous travaillerez au quotidien avec des clients entreprises français, aussi bien au niveau des dirigeants qu'au niveau ingénierie Plus de 6 ans d'expérience en tant qu'ingénieur·e logiciel, architecte de solutions, ingénieur·e en déploiement avancé ou fondateur·rice technique Une expérience dans un poste d'avant-vente ou de conseil technique auprès de grandes entreprises, idéalement sur le marché français, y compris la définition du périmètre et la conception de solutions complexes Une expérience dans la vente basée sur la valeur, ce qui signifie que vous êtes en mesure d'élaborer un dossier commercial, de quantifier l'impact et de le présenter à des décideurs de haut niveau L'aisance à présenter et à établir des relations avec des parties prenantes de niveau C et VP Une expérience dans la prise en charge de la réussite technique des transactions avec les entreprises : évaluations, preuves de concept et audits techniques préalables avec les équipes d'ingénierie, de sécurité, juridique et des achats Une expérience en production avec des applications propulsées par des LLM, incluant le prompting, l'ingénierie du contexte, les architectures d'agents, les cadres d'évaluation et le déploiement à grande échelle Une expérience pratique en ingénierie, incluant la conception et le déploiement d'applications en production, afin de pouvoir échanger avec les responsables techniques et leurs équipes Une familiarité avec les exigences en matière de sécurité, de conformité et d'architecture d'entreprise, et une expérience dans la résolution de ces problématiques avec les équipes clientes La capacité à expliquer clairement des concepts complexes d'IA à des publics techniques et dirigeants, et à naviguer entre des secteurs tels que les services financiers, les soins de santé, le commerce de détail et l'industrie manufacturière Un intérêt marqué pour la mise en place de technologies puissantes sûres et bénéfiques About the role As an Applied AI Engineer on our Enterprise team, your role is to guide some of France's largest businesses to the frontier of AI and help them deploy Claude into their operations, their products, and their ways of working. You will become the go-to Claude Platform specialist and trusted technical advisor for your customers, advising their engineering teams on architecture, agent design, and evaluation, and working with the C-level and senior executives who sponsor these programmes to show the business value Claude can create and help them reach a confident decision to build on Claude. Enterprise deals are different. Procurement cycles are longer, more stakeholders are involved, and success depends on being able to connect the technical work to the outcomes the boardroom cares about. You will be as comfortable advising an engineering team on evaluation and architecture as you are presenting a value case to a CIO or CTO, and you will carry the technical thread across every stage of a multi-quarter engagement. Much of this work happens in French, with French executives and engineering teams, so native or fluent French is essential for the role. You will partner closely with Enterprise Account Executives and Applied AI Architects to take each customer from first conversation, through technical evaluation, proof of value and procurement, to the decision to build on Claude. Once they have decided, you set their systems integration partner up to deliver, agreeing the target architecture and what good looks like, and you stay close as the customer's technical advisor on Claude throughout deployment, while the partner does the build. Working alongside Anthropic's Product and Engineering teams, you will use your knowledge of the Claude Platform to advise on evaluation, recommend architectures that meet enterprise security and scale requirements, and create the technical and business resources that help large organisations succeed with Claude. Responsibilities Partner with Enterprise Account Executives and Applied AI Architects to take enterprise customers in France from first conversation, through technical evaluation, proof of value and procurement, to the decision to build on Claude Lead the technical side of each opportunity through to that decision, and remain the customer's technical advisor on Claude as they deploy Set customers and their systems integration partners up to deliver: agree the target architecture, define what good looks like, and stay on hand to advise the delivery team as the build progresses Guide enterprise customers to the frontier of AI, advising them on how to deploy Claude into their operations, their products, and their ways of working Help customer engineering teams see how they would build on Claude, covering architecture, agent design and evaluation, so they can make a confident decision Build and present the business value case for Claude with C-level and senior executives, in French and English, linking technical capabilities to measurable outcomes such as cost, revenue, risk, and time to market Guide customers through long, multi-stakeholder procurement and adoption cycles, including technical evaluations, proofs of concept, security and architecture reviews, and a clear path to production Work with Account Executives on account strategy, deal qualification, and executive engagement plans, and with Applied AI Architects to keep context and continuity across every engagement Run executive briefings, technical workshops, and enablement sessions for both leadership and engineering audiences Navigate enterprise requirements around security, compliance, data residency, and governance, working with Anthropic's internal teams where needed Identify patterns across enterprise engagements and feed insights back to Product, Engineering, and the wider Applied AI team Travel to customer sites across France for executive meetings, workshops, and relationship building You may be a good fit if you have Native or fluent French, written and spoken, as you will work day to day with French enterprise customers at both executive and engineering level 6+ years of experience as a Software Engineer, Solutions Architect, Forward Deployed Engineer, or technical founder Experience in a pre-sales or technical advisory role selling into large enterprises, ideally in the French market, including scoping and designing complex solutions Experience with value-based selling, meaning you can build a business case, quantify impact, and present it to senior decision makers Comfort presenting to, and building relationships with, C-level and VP-level stakeholders Experience owning the technical win in enterprise deals: evaluations, proofs of concept and technical due diligence with engineering, security, legal and procurement teams Production experience with LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale A hands-on engineering background, including building and deploying production applications, so you can relate to engineering leaders and their teams Familiarity with enterprise security, compliance, and architecture requirements, and experience working through them with customer teams The ability to explain complex AI concepts clearly to both technical and executive audiences, and to move between industries such as financial services, healthcare, retail, and manufacturing A passion for making powerful technology safe and beneficial The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: €220.000 — €235.000 EUR Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Ukraine; Poland; Spain; Portugal; Germany; Romania At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. And now we are looking for a Engineering Manager, Applied AI & Machine Learning Engineering to join us as part of our team. About Role PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. As an Engineering Manager, AI/ML, you will support a cross-functional team of MLE and MLOps engineers working across several AI/ML initiatives. Your primary focus will be resource planning, execution, and people management. You will work closely with project leads, technical leads, functional managers, and product partners to ensure projects are appropriately staffed, plans are realistic, risks are visible, and teams can deliver effectively. You will manage capacity and resource allocation across multiple projects, help coordinate dependencies and priorities, and provide stakeholders with a clear view of delivery progress. Project and technical leads will continue to own product direction and technical decisions. You will also support the career growth and performance of team members. This includes gathering feedback, coaching employees, creating development plans, and contributing to performance, promotion, and compensation reviews. You should have enough AI/ML experience to understand the work, communicate effectively with engineers, and identify technical delivery risks. However, this is not expected to be a hands-on engineering or architecture role. Our Tech Stack & Focus Areas Generative AI & LLMs: Develop and maintain LLM-based solutions for generative features. Classic ML Models: Develop and maintain predictive and classification models for financial data Vector Databases: Implementing efficient storage and retrieval systems for high-dimensional data embeddings. Embeddings: Developing hybrid models to extract insights from diverse data sources. High-Volume Data Management: Engineering systems capable of handling massive, real-time data streams. Work Environment Flexible schedule with participation in team ceremonies and cross-functional collaboration. Time zone: Europe/Kyiv. As a qualified expert, You will: Manage resource allocation and capacity planning across multiple AI/ML projects and operational commitments Partner with project and technical leads to create realistic delivery plans, milestones, and staffing models Maintain a clear view of project progress, dependencies, risks, and resource constraints Help resolve delivery blockers, priority conflicts, and cross-team dependencies Facilitate quarterly and ongoing planning across MLEs and MLOps teams Provide clear delivery and staffing updates to functional managers and other stakeholders Manage and coach engineers through regular one-to-one meetings and career discussions Gather and synthesize feedback from project leads, technical leads, and cross-functional partners Create development plans and support performance, promotion, and compensation review processes Identify team capability gaps and contribute to hiring, onboarding, retention, and workforce planning Foster an inclusive, collaborative, and high-performing team environment Apply Agile, Lean, and Fast-Flow practices to improve team effectiveness and delivery predictability We’re looking for you if you have At least three years of experience in software engineering, AI/ML, or a related field At least three years of experience in people management, engineering management, or technical program leadership Working knowledge of AI/ML modeling, systems and the development lifecycle Experience managing multiple technical projects with shared resources and cross-team dependencies Strong skills in capacity planning, resource allocation, project execution, risk management, and stakeholder communication Experience supporting the performance and career development of technical employees Ability to understand technical discussions and work effectively with MLE and MLOps teams Experience working with distributed or geographically dispersed teams English — Upper Intermediate or higher; Ukrainian — fluent Bonus points Experience managing or supporting MLE and MLOps teams Experience working in a matrix organization with separate people, project, product, and technical leadership roles Experience with planning or allocating engineers across multiple projects Familiarity with production ML, generative AI, semantic search, summarization, prediction, or similar capabilities Familiarity with technologies such as Kubernetes, Docker, Kafka, Airflow, Snowflake, and cloud platforms Experience conducting performance reviews and building employee development plans Experience working with staffing partners, contractors, or blended internal and external teams Experience in fintech, SaaS, market data, or another data-intensive industry What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling clients growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Work fully remote around the globe, or in a hybrid work model from our office hubs which are equipped with everything needed for comfortable work. Enjoy a flexible working schedule and create work and rest balance for yourself. Empower yourself with a stable workload and a stable income, focusing on lasting cooperation and high-performance culture. Embrace the opportunity for personal and professional growth Take advantage of performance review and career path. Elevate your skills with mentorship program, personal development plan, and individual learnings through the corporate library, public speaking support, and more. Feel cared about Be among like-minded people and feel supported with collaboration, open communication and mutual respect. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Interview Steps: Interview with the recruiter Codebase review Interview System design Interview Cross-functional execution case Interview Final сlient Interview

Location: Munich, Germany About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Engineer on our Enterprise team, your role is to guide some of Germany's largest businesses to the frontier of AI and help them deploy Claude into their operations, their products, and their ways of working. You will become the go-to Claude Platform specialist and trusted technical advisor for your customers, advising their engineering teams on architecture, agent design, and evaluation, and working with the C-level and senior executives who sponsor these programmes to show the business value Claude can create and help them reach a confident decision to build on Claude. Enterprise deals are different. Procurement cycles are longer, more stakeholders are involved, and success depends on being able to connect the technical work to the outcomes the boardroom cares about. You will be as comfortable advising an engineering team on evaluation and architecture as you are presenting a value case to a CIO or CTO, and you will carry the technical thread across every stage of a multi-quarter engagement. Much of this work happens in German, with German executives and engineering teams, so native or fluent German is essential for the role. You will partner closely with Enterprise Account Executives and Applied AI Architects to take each customer from first conversation, through technical evaluation, proof of value and procurement, to the decision to build on Claude. Once they have decided, you set their systems integration partner up to deliver, agreeing the target architecture and what good looks like, and you stay close as the customer's technical advisor on Claude throughout deployment, while the partner does the build. Working alongside Anthropic's Product and Engineering teams, you will use your knowledge of the Claude Platform to advise on evaluation, recommend architectures that meet enterprise security and scale requirements, and create the technical and business resources that help large organisations succeed with Claude. Responsibilities Partner with Enterprise Account Executives and Applied AI Architects to take enterprise customers in Germany from first conversation, through technical evaluation, proof of value and procurement, to the decision to build on Claude Lead the technical side of each opportunity through to that decision, and remain the customer's technical advisor on Claude as they deploy Set customers and their systems integration partners up to deliver: agree the target architecture, define what good looks like, and stay on hand to advise the delivery team as the build progresses Guide enterprise customers to the frontier of AI, advising them on how to deploy Claude into their operations, their products, and their ways of working Help customer engineering teams see how they would build on Claude, covering architecture, agent design and evaluation, so they can make a confident decision Build and present the business value case for Claude with C-level and senior executives, in German and English, linking technical capabilities to measurable outcomes such as cost, revenue, risk, and time to market Guide customers through long, multi-stakeholder procurement and adoption cycles, including technical evaluations, proofs of concept, security and architecture reviews, and a clear path to production Work with Account Executives on account strategy, deal qualification, and executive engagement plans, and with Applied AI Architects to keep context and continuity across every engagement Run executive briefings, technical workshops, and enablement sessions for both leadership and engineering audiences Navigate enterprise requirements around security, compliance, data residency, and governance, working with Anthropic's internal teams where needed Identify patterns across enterprise engagements and feed insights back to Product, Engineering, and the wider Applied AI team Travel to customer sites across Germany for executive meetings, workshops, and relationship building You may be a good fit if you have Native or fluent German, written and spoken, as you will work day to day with German enterprise customers at both executive and engineering level 6+ years of experience as a Software Engineer, Solutions Architect, Forward Deployed Engineer, or technical founder Experience in a pre-sales or technical advisory role selling into large enterprises, ideally in the German market, including scoping and designing complex solutions Experience with value-based selling, meaning you can build a business case, quantify impact, and present it to senior decision makers Comfort presenting to, and building relationships with, C-level and VP-level stakeholders Experience owning the technical win in enterprise deals: evaluations, proofs of concept and technical due diligence with engineering, security, legal and procurement teams Production experience with LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale A hands-on engineering background, including building and deploying production applications, so you can relate to engineering leaders and their teams Familiarity with enterprise security, compliance, and architecture requirements, and experience working through them with customer teams The ability to explain complex AI concepts clearly to both technical and executive audiences, and to move between industries such as financial services, healthcare, retail, and manufacturing A passion for making powerful technology safe and beneficial Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Paris, France About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. À propos d’Anthropic La mission d’Anthropic est de créer des systèmes d’IA fiables, interprétables et orientables. Nous voulons que l'IA soit sûre et bénéfique pour nos utilisateurs et pour la société dans son ensemble. Notre équipe est composée de chercheurs, d'ingénieurs, d'experts politiques et de chefs d'entreprise engagés qui travaillent ensemble pour créer des systèmes d'IA bénéfiques. À propos du poste En tant qu'architecte des solutions partenaires au sein de l'équipe d'IA appliquée d'Anthropic, vous serez architecte avant-vente chargé d'entretenir des relations techniques avec nos intégrateurs de systèmes mondiaux et régionaux (GSI/RSI) et nos partenaires cloud (AWS et GCP). Vous renforcerez nos relations avec les partenaires clés pour accélérer les revenus indirects, permettre leurs pratiques d'IA et exécuter la stratégie GTM à long terme. Responsabilités: Partenariat technique stratégique : soyez un partenaire de réflexion technique pour l'équipe des partenariats Anthropic GTM, en apportant une expertise technique pour mieux comprendre l'environnement des partenaires, en pilotant des programmes stratégiques clés et en identifiant des opportunités pour approfondir leurs compétences techniques. Vous vous intégrez aux équipes techniques de GSI et des partenaires cloud pour mettre en œuvre leurs pratiques en matière d'IA, vous aider à résoudre les problèmes, promouvoir Anthropic au sein de leurs communautés de développeurs et servir de point d'accès pour les problèmes techniques complexes. Développement conjoint de solutions : Collaborer avec des partenaires pour identifier des applications GenAI spécifiques à grande valeur industrielle, développer des solutions conjointes et codifier des architectures de référence / bonnes pratiques afin d’accélérer le temps de déploiement Assistance aux offres clients : Intervenir directement pour débloquer des transactions clients stratégiques où les partenaires sont le principal vecteur de livraison, apportant une expertise technique approfondie et des conseils en architecture de solutions. Écosystème de partenaires et événements : représentez Anthropic lors d'événements partenaires tels que les ateliers clients GSI, les sommets AWS et les conférences sectorielles. Animer ou soutenir des événements, hackathons et sessions de formation technique destinés aux développeurs partenaires, en particulier pour les communautés ayant une expertise technique pointue. Retours sur les produits : validez et recueillez des retours sur les produits et services d'Anthropic, notamment en ce qui concerne les cas d'utilisation et modèles de déploiement des partenaires, et transmettez ces commentaires aux équipes Anthropic concernées afin d'éclairer la feuille de route du produit et la stratégie des partenaires. Profil recherché: Plus de 5 ans d'expérience dans des rôles techniques orientés clients et partenaires, tels que Architecte de Solutions, Ingénieur Commercial, Ingénieur Commercial Partenaires, Responsable de Compte Technique Expérience avérée de partenariats fructueux avec des intégrateurs de systèmes mondiaux et/ou des fournisseurs de services cloud pour résoudre des problèmes techniques complexes, de la conception initiale de la solution à sa mise en œuvre chez le client Capacité exceptionnelle à établir des relations avec diverses parties prenantes et à leur communiquer des concepts techniques, notamment des cadres supérieurs, des équipes informatiques et d'ingénierie, etc. Solides compétences en présentation et communication technique avec la capacité de traduire les exigences entre parties prenantes techniques et commerciales Expérience de la conception d'architectures cloud évolutives et de l'intégration avec des systèmes d'entreprise Familiarité avec les cadres et outils LLM courants ou une formation en apprentissage automatique ou en science des données Enthousiasme à l'idée de participer à une collaboration inter-organisationnelle, de trouver des compromis et de trouver un équilibre entre des priorités concurrentes L'amour de l'enseignement, du mentorat et de la réussite des autres Passion pour la réflexion créative sur la manière d'utiliser la technologie de façon sûre et bénéfique, et qui favorise ultimement l'avancement des systèmes d'IA sûrs. About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI Architect on the Partnerships team at Anthropic, you will be a pre-sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Responsibilities: Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events: Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities.Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. You may be a good fit if you have: 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: €190.000 — €220.000 EUR Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Munich, Germany About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a pre-sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with both the Claude API and Claude for Work Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel occasionally to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager Native or C1 German speaker with fluent English proficiency Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Comfortable with python Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Deadline to apply: None. Applications will be reviewed on a rolling basis. Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Bellevue Workplace: OnSite LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? Your Mission At UiPath, we believe the next generation of software won't simply automate tasks—it will reason, plan, adapt, and act autonomously. As a Principal Applied Scientist, you'll help invent that future. You will lead the research and development of frontier AI systems that combine foundation models, multimodal reasoning, agentic workflows, and post-training techniques to build autonomous software capable of operating enterprise applications like a human. This is an individual contributor leadership role for scientists who enjoy building. You'll work at the intersection of applied research and production engineering—designing new algorithms, training and evaluating large models, developing novel post-training methods, and shipping systems that reach enterprise customers. If you're passionate about pushing the limits of LLMs, multimodal models, reasoning, planning, tool use, and AI agents—and you enjoy transforming research into products—this is the role for you. About the Team Our Advanced Machine Learning organization is building large multimodal foundation models capable of understanding enterprise software, reasoning over complex workflows, planning long-horizon tasks, and autonomously interacting with digital systems. Our work spans: - Foundation models - Agentic AI - Multimodal reasoning - Reinforcement learning - Post-training - Model alignment - Evaluation systems - Enterprise AI agents Our mission is to advance practical general intelligence for enterprise automation. What You'll Do - Lead research and development of large-scale foundation models and agentic AI systems for enterprise automation. - Design novel approaches for post-training, model alignment, reinforcement learning, preference optimization, and synthetic data generation. - Develop scalable evaluation frameworks that measure reasoning, tool use, planning, and autonomous task completion. - Build production-quality AI systems that combine LLMs, multimodal models, retrieval, planning, memory, and external tool use. - Drive innovations in long-context reasoning, workflow generation, autonomous software interaction, and multi-agent orchestration. - Design large-scale experiments, analyze model behavior, and iterate using data-driven evaluation. - Collaborate closely with engineering and product teams to transition research into production systems. - Mentor scientists and engineers while raising the technical bar across the organization. - Influence UiPath's long-term AI strategy through technical leadership and scientific innovation. What We're Looking For We're looking for scientists who have successfully taken frontier AI research from idea to production. The ideal candidate has deep expertise in several of the following: - Foundation model training - LLM post-training - Reinforcement Learning from Human Feedback (RLHF) - Preference optimization (DPO, PPO, GRPO or similar methods) - Reward modeling - Synthetic data generation - Model evaluation - Agentic reasoning - Tool use - Function calling - Long-horizon planning - Multimodal learning - Retrieval-Augmented Generation (RAG) - Distributed training and inference - Large-scale PyTorch systems - Model alignment and safety Preferred Experience - PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, Statistics, Robotics, or a related discipline. - Significant experience building and deploying production AI systems based on large language models or multimodal foundation models. - Demonstrated ownership of end-to-end ML systems—from research and experimentation through production deployment. - Strong programming skills in Python and deep experience with modern ML frameworks such as PyTorch. - Experience training or fine-tuning large models using distributed compute infrastructure. - Strong publication record or demonstrated technical leadership in applied AI is highly valued. - Excellent communication skills and the ability to influence technical direction across organizations. Technologies We Work With While experience with every technology is not expected, many members of our team work with: - PyTorch - JAX - CUDA - vLLM - Ray - DeepSpeed - FSDP - Triton - LangGraph - Semantic Kernel - MCP - Vector databases - Kubernetes - Azure AI - Hugging Face - Distributed GPU training infrastructure You'll Thrive Here If You... - Love building AI systems—not just publishing papers. - Enjoy tackling ambiguous, first-principles problems. - Are excited by rapidly evolving research. - Think deeply about evaluation as much as modeling. - Care about elegant engineering as much as novel algorithms. - Want your research to power products used by millions of people. #LI-MH1 Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the Role: We are seeking an exceptional Applied Scientist to join our Applied Science team. In this role, you will design, develop, and deploy the algorithmic systems that power Garner's products and drive meaningful impact for our members. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them. This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund. What you will do: Own the most ambiguous, high-stakes problems on the team end-to-end, and serve as a technical resource others rely on Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for Find novel ways to frame and solve the team's hardest problems, proving out approaches that others build on Set the bar for quality by reviewing others' work with rigor, and build the standards and evaluation tooling the team relies on Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are three problems on our near-term roadmap: Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions. AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely. Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. What we're looking for: 4+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 2+ years of industry experience with a relevant advanced degree, PhDs preferred A bias toward action, quickly translating ideas into working prototypes to test approaches Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them Deep technical range, with fluency across Garner's data and a habit of staying current with advances in the field Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem Strong communication skills and the ability to synthesize complex algorithmic ideas for senior and external stakeholders, and to secure buy-in for cross-team work A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback What you'll get here You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment. This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare. Compensation Transparency: The target base comp range for this position is $200,000 – $230,000 . Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role: We are seeking an exceptional Applied Scientist III to join our Applied Science team. Garner is hiring Applied Scientists to design and ship the algorithmic systems at the core of our product. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them. This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Ship production algorithmic systems end-to-end, from problem framing to launch to iteration Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for Bring new ideas to your work, experimenting with approaches beyond the obvious to get better results Produce rigorous, well-validated work others can rely on, and review your peers' code and analyses Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are three problems on our near-term roadmap: Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions. AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely. Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. What we're looking for: 2+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent advanced degree A bias toward action, quickly translating ideas into working prototypes to test approaches Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them A solid command of the methods your work calls for and the data your models depend on Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem Strong communication skills, with the ability to present your work clearly to senior stakeholders A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback What you'll get here You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment. This is a unique opportunity to work on high-impact search problems in healthcare, helping shape how members find better care through algorithmic systems that directly influence healthcare outcomes. Compensation Transparency: The target base comp range for this position is $158,000 – $190,000 . Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role: We are seeking an exceptional Manager, Product Applied Science to build and lead a team at the core of Garner's product. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them. This is a hands-on management role. You are responsible for the overall technical direction of your squad, building alongside your team of Applied Scientists to solve some of the hardest problems at the company. This is not a dashboards or descriptive-analytics team. Your team owns production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is leading a research pod at a top hedge fund. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Lead a team of 4-6 — hire, coach, and develop them, hold the bar on both rigor and speed, and help raise that bar across Applied Science Own the Population Health team and their outputs as a core responsibility Own your team's roadmap and delivery: what gets built, in what order, and whether it ships Set technical direction, and get in the weeds to do it — stay close enough to the code and the data to call the approach yourself, whether that's machine learning, optimization, a heuristic, or a simple rule, and set the standard for how your team makes that call Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship Put your own hands on the problems where your judgment matters most — the highest-stakes, least-defined work — and deliver the algorithmic step-changes that move metrics like total-cost-of-care savings, steerage, and member engagement Turn ambiguous business goals into a clear problem set alongside Research, Product, Engineering, and business stakeholders, and represent your team's work to senior leadership Set the quality bar: review your team's work with rigor, and define the metrics that decide whether a solution is working Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are three problems on our near-term roadmap: Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions. AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely. Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. The ideal candidate has: 6+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant advanced degree, PhDs preferred Deep technical credibility, with the range and judgment to lead scientists who are experts in their own right, and the willingness to stay hands-on Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them A bias toward action, quickly translating ideas into working prototypes to test approaches Strong communication skills, including at the executive level, with a track record of driving alignment across teams and functions A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback Technologies we use: Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment. This is a unique opportunity to build and lead the team behind Garner's algorithmic systems — shaping how members find better care, and how applied science gets done at Garner, while staying close to the work yourself. What you'll get here: You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Compensation Transparency: The target base comp range for this position is $300,000-$390,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: New York City, New York What you’ll be part of Garner is on a mission to transform the U.S. healthcare system — and we’re the only proven player doing exactly that. We partner with employers to redesign how healthcare works: applying 550+ proprietary clinical metrics across 80+ specialties to a dataset of 320M+ patients to identify the best-performing doctors, then using compelling incentives to steer members to the care that helps them get healthier, faster. The result is a rare “win win” — better care and lower costs for both members and employers. In just five years, our work has helped over 2.5 million people access higher-quality care and saved $1B in healthcare costs. We recently raised our Series E and have doubled five years running. If you've ever wanted your work to solve a problem that touches every person in this country, this is the opportunity to do exactly that. You'd be joining a team fundamentally reimagining healthcare in the U.S. — and using AI to scale that impact further and faster than anyone else can. About the role: We are seeking an exceptional Staff Applied Scientist to join our Applied Science team. Garner is hiring Applied Scientists to design and ship the algorithmic systems at the core of our product. Our members rely on us to answer hard questions — Which doctor should I see? What will it cost? When should we reach out, and how? — and the quality of those answers is determined by the algorithms behind them. This is not a dashboards or descriptive-analytics role. You will own production systems end-to-end: framing the problem, defining the objective function, choosing the right approach (ML, optimization, heuristics, expert systems, or a hybrid), shipping it, and improving it against real-world outcomes. The closest analog outside healthcare is a quantitative researcher at a top hedge fund. This is a player-coach role. You will be a hands-on-keys Applied Scientist, while also leading a small team that helps you deliver on your roadmap. Your time will be split between your own technical work and working with your team to shape how they approach their problems. This role is a good fit for someone who wants to develop their management toolkit while continuing to work closely on their own technical work, and it can lead either towards management or a deeper senior IC track. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Own the most ambiguous, high-stakes problems facing the company end-to-end, and set how the team frames and approaches them Frame messy, real-world healthcare and business constraints into clear objectives, tradeoffs, and decision frameworks Define the set of metrics needed to judge whether a solution is working, and validate solutions before they ship Choose the right approach for each problem, from machine learning to optimization to heuristics to simple rules, based on what the problem actually calls for, and set the standard for how the team selects and applies these approaches Deliver algorithmic breakthroughs that move the company's most important metrics, pioneering approaches that become how applied science is done at Garner Lead a small team — set their technical direction, unblock them when they're stuck, and share accountability for their growth and the quality of what they ship Review Applied Science work at the highest level across the company, ensuring the methods used across teams are sound and correctly applied Build a deep understanding of the healthcare economy and Garner's place in it To make the role concrete, here are three problems on our near-term roadmap: Provider tiering optimization. Build a tiering algorithm that jointly optimizes geographic access and total-cost-of-care savings across our doctor network. The objective function, constraints, and tradeoff surface are all open design questions. AI primary care doctor. Fine-tune and productionize an LLM-based primary care experience on our website, including the evaluation harness, guardrails, and ongoing quality monitoring needed to ship a medical-adjacent product safely. Member engagement model. Build an ML system that ingests claims data and in-app behavior to choose the right channel and moment for each touchpoint — SMS, push, phone, or email — to influence member behavior toward better-quality, lower-cost care. The ideal candidate has: 6+ years of industry experience as an Applied Scientist, Machine Learning Engineer, Research Scientist, or equivalent; or 4+ years of industry experience with a relevant advanced degree, PhDs preferred A bias toward action, quickly translating ideas into working prototypes to test approaches Strong applied problem-solving skills, with the ability to define good metrics and then deliver solutions that improve them Recognized technical authority, with the judgment to ensure the techniques used across an organization are sound Strong interest in mentoring or technically leading other Scientists — formal management experience is welcome, but not required Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem Strong communication skills, including at the executive level, with a track record of driving alignment across an organization A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback What you’ll get here You’ll work on problems that matter, at a company working to change healthcare at scale. You’ll work at the intersection of AI and systemic healthcare reform, where the problems we solve are as interesting and compelling as the mission. At Garner, you’ll take on real, ambitious problems with real ownership and autonomy, alongside exceptional, principles-based people who genuinely want you to win. It’s demanding by design. You’ll be challenged to stretch beyond what you thought possible and receive consistent coaching to help you grow and do the best work of your career. This isn't the right fit for everyone, and that's intentional. The people here are driven by what's at stake for real people, and that's what gives our intensity its purpose. Technologies we use: Python, SQL, AWS, Snowflake, pandas, XGBoost, PyTorch, HuggingFace, modern LLM tooling and eval frameworks. We pick tools based on the problem, not the resume — bring your judgment. This is a unique opportunity to work on high-impact problems in healthcare — shaping how members find better care through algorithmic systems that directly influence healthcare outcomes, and helping the scientists around you do the same. Compensation Transparency: The target base comp range for this position is $300,000-$390,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more. Fraud and Security Notice: Please be aware of recent job scam attempts. Our recruiters use getgarner.com and garnerhealth.com email domains exclusively. If you have been contacted by someone claiming to be a Garner recruiter or a hiring manager from a different domain about a potential job, please report it to law enforcement here and to candidateprotection@garnerhealth.com . Equal Employment Opportunity: Garner Health is proud to be an Equal Employment Opportunity employer and values diversity in the workplace. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. Garner Health is committed to providing accommodations for qualified individuals with disabilities in our recruiting process. If you need assistance or an accommodation due to a disability, you may contact us at talent@garnerhealth.com .

Location: Paris; Singapore ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As an Applied AI Engineer on the Proto team, you will lead the design and delivery of robust, production-grade AI systems in rapid development cycles. The Proto team sits at the intersection of product and customer, turning advanced technology into meaningful, real-world solutions. You will be deeply involved in both client-facing and internal projects, ensuring Mistral’s capabilities directly address business needs and drive measurable value. You will translate complex, often ambiguous business requirements into engineered solutions that work at scale. In this role, you guide technical decisions, collaborate closely with internal teams and customers, and help shape product direction by pressure-testing what’s possible. Your work will unlock new business opportunities and help drive continuous product improvement. WHAT YOU WILL DO - Deliver end-to-end full-stack AI solutions from project scoping through deployment - Partner with customers to clarify needs, define requirements, and architect robust systems - Ship ready-to-use applications for both clients and Mistral’s internal teams - Lead architecture and technical choices, ensuring solutions are scalable and reliable - Diagnose and solve complex technical problems across various industries and use cases - Contribute to internal tools, product improvements, and open-source initiatives - Evaluate and integrate new technology capabilities into existing systems WHAT WE'RE LOOKING FOR - At least 2 years building and deploying production AI products or systems - Strong experience with vibe coding tool, with high regards for clean code & high architecture standards - Experience working with modern GenAI stacks with expertise in RAG, Agent, Evaluation & Orchestration. - Strong Python skills, with experience in scalable backend frameworks like FastAPI - Familiarity with frontend development, ideally using frameworks such as React or Vue - Ability to quickly understand business needs and translate them into technical plans - Skilled at explaining complex technical ideas to diverse stakeholders - Track record of collaborating effectively across different teams WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success Support customers building with both the Claude API and Claude for Work Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases Identify common integration patterns and contribute insights back to our Product and Engineering teams Travel occasionally to customer sites for workshops, technical deep dives, and relationship building Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Comfortable with python Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Please note this role requires 3 days in office per week. Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $240,000 — $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Amsterdam, Netherlands; London, United Kingdom; Remote - Europe; Zurich, Switzerland About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. We are seeking a Staff Applied AI Researcher to join a fast-growing team building an agent-native search platform - the web access layer for AI systems. You can think of this as Google search, but for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing these systems to search and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval, ranking and passage extraction under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24/7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. In the first year, you will own a specific part of the search stack, e.g. ranking or iterative retrieval. What you'll work on: Designing an agent-native search system that handles everything from low-latency single-hop search to complex deep search tasks requiring iterative planning, querying, refinement and reasoning. Training ranking and retrieval models optimized for agent-driven workflows under real world constraints Bringing the latest advances from the research community to our search stack and ship it to production. Your responsibilities: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi-stage retrieval architectures (query understanding, rewriting, retrieval, reranking and iterative retrieval) Lead experimentation on modern retrieval approaches (embedding research, sparse and hybrid retrieval, reranking, context compression) and bring them into production Develop methods for grounding LLMs in real-time web data at scale, using trust, quality and freshness signals to surface reliable sources Partner with the evaluation team to define new metrics for agentic systems, where correctness is not reducible to clicks Analyze trade-offs across relevance, latency, and cost, and work closely with engineering to deploy systems that operate at web scale Mentor researchers and engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking or building RAG-based assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM-integrated or knowledge-intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python Top-tier publications ( ICLR , ICML , NeurIPS, AAAI , EMNLP , ACL ) Ability to operate in a fast-moving, product-driven environment with high ownership and autonomy Nice to haves Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RL post-training of LLMs or VLMs Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Location: Palo Alto; New York Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE   Mistral AI is seeking Applied Scientists and Research Engineers to drive innovative research and collaborate with clients on complex research projects. You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas you will apply these models across a diverse set of use cases and domains. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions that turn the needle.   WHAT YOU WILL DO   • Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. You don’t panic when you see OOM errors or when NCCL feels like not wanting to talk. • Generate and curate data for pre-training and post-training, working on evaluations and making sure the model’s performance beats expectations. • Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. • Collaborate with cross-functional teams to tackle complex use cases using agents and RAG pipelines. • Manage research projects and communications with client research teams.   WHAT WE'RE LOOKING FOR     • You have excellent communication skills. You are at ease explaining complex technical concepts to both technical and non-technical audiences. • You’re an expert with PyTorch or JAX. • You’re not afraid of contributing to a big codebase and can find yourself around independently with little guidance. • You write clean, readable, high-performance, fault-tolerant Python code. • You don’t need roadmaps: you just do. You don’t need a manager: you just ship. • Low-ego, collaborative and eager to learn. • You have a track record of success through personal projects, professional projects or in academia.   NICE TO HAVE     • Hold a PhD / master in a relevant field (e.g., Mathematics, Physics, Machine Learning, Computer Science & Engineering), but if you’re an exceptional candidate from a different background, you should apply. • Can bring a variety of research experience (agents, multi-modality, robotics, diffusion, time-series). • Have contributed to a large codebase used by many (open source or in the industry). • Have a track record of publications in top academic journals or conferences. • Love improving existing code by fixing typing issues, adding tests and improving CI pipelines.     WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Paris; Amsterdam; London; Lausanne Workplace: Hybrid ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE Mistral AI is seeking Applied Scientists and Research Engineers to drive innovative research and collaborate with clients on complex research projects. You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas you will apply these models across a diverse set of use cases and domains. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions that turn the needle. We are made of researchers, engineers, product builders, ex-founders who love tackling the most complex real world problems in the industry.   WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. - Work across a diverse set of complex real world problems such as robotics, engineering, finance, cybersecurity, physics and more. - Generate and curate data for pre-training and post-training, working on evaluations and making sure the model's performance beats expectations. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases using agents and retrieval pipelines. - Manage research projects and communications with client research teams.   WHAT WE'RE LOOKING FOR - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - Ex-founder or builder - PhD / Master in a relevant field (Mathematics, Physics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Research experience in agents, multimodal models, world models, robotics, diffusion models, cybersecurity, 3D understanding/generation, or time-series analysis. - Experience working on large code bases or large machine learning models at scale. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: Montréal ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. Role Summary We are seeking an Applied AI, Forward Deployed Engineer to build customer use cases on top of the Mistral stack. You will turn "we have agents" into "we shipped something a client uses." This role is about composing cybersecurity-related agentic workflows, configuring harnesses for real-world scenarios, and delivering value directly to clients. As a Forward Deployed Engineer at Mistral, you may also work on use cases outside cybersecurity, bringing the same context engineering, orchestration, and eval work to enterprise workflows in finance, manufacturing, defense, or the public sector. What You Will Do - Client-Facing Agentic Solutions - You'll individually help deploy into production use cases with considerable business impact across various industries, with cybersecurity client assignments as a priority - You'll work on state-of-the-art GenAI applications, driving a crucial technological transformation together with our customers - Tackle iconic use cases that no existing solution on the market can address - from custom configuration of cybersecurity harnesses for cloud defense, to optimizing agentic vulnerability scanning solutions, to customizing agentic red-teaming solutions or penetration testing scenarios - You'll work directly on client use cases, translating security requirements into agentic solutions - You'll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations, providing technical guidance on our products and explaining Mistral technologies to various stakeholders - You'll collaborate with our product and science teams to continuously improve our product and model capabilities based on customer feedback How We Work in Applied AI - We care about people and outputs - What matters is what you ship, not the time you spend on it - Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week - Always ask why. The best solutions come from deep understanding, not from copying what worked before - We say what we mean. Feedback is direct, timely, and given because we care - No politics. Low ego, high standards - We embrace an unstructured environment and find joy in it About You - You are fluent in English - You have 2+ years as a technical individual contributor (data scientist or software engineer) on AI-based products - You have proven experience in AI or machine learning product implementation with APIs, back-end, and front-end interfaces - You have experience tackling advanced RAG, building agentic use cases, or fine-tuning LLMs - You have a deep understanding of the concepts and algorithms underlying machine learning and LLMs - You have strong technical coding skills in Python - You have strong communication skills, with an ability to explain complex technical concepts in simple terms to both technical and non-technical audiences Ideally, you have: - Contributed to open-source projects, in particular in the space of LLMs - Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager - Hands-on experience building agents, LLM orchestration, context engineering, evals, and RAG systems - A bias toward action and delivery - you ship fast - The ability to operate independently with a customer-led mindset - The ability to reuse internal building blocks and components effectively - Strong problem-solving abilities and attention to detail - A collaborative attitude - Pentesting knowledge - Experience developing a cybersecurity product - Experience building agentic harnesses or multi-agent systems end-to-end - A strong background in evals and benchmarking of agent systems - Experience with security tooling or workflows - Prior work on production AI systems in regulated or high-stakes environments WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.