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Location: Athens, Greece Are you a passionate IT Consultant with expertise in Artificial Intelligence (AI) and Machine Learning (ML)? We’re seeking a dynamic professional to join our team, either at our Athens offices or remotely. This role provides an exciting opportunity to work on challenging IT software projects for major international public organizations alongside a highly skilled team What You'll Do: Participate in requirements elicitation meetings and contribute to brainstorming sessions; Elaborate functional/non-functional specifications; Analyze data originating from various data sources, in order to drive optimization and improvement of product development and business strategies; Identify candidate models and algorithms matching the business problems; Develop PoC and enterprise solutions; Contribute to the full development lifecycle, through requirements gathering, analysis, design, implementation, testing, documentation, and maintenance of system components; Operate in a multinational environment, adhering to highly professional standards and methods; Ensure the delivery of quality products. Requirements University degree in Data Science, Computer Science, Information Technology, or other related fields; Good understanding of a variety of AI and machine learning techniques and their real-world advantages/drawbacks; Good understanding of data modeling and evaluation; Good understanding of the ML lifecycle; Experience with Exploratory Data Analysis (EDA); Strong analytical capabilities, team and quality-oriented, keen to learn and excel; Excellent written and oral communication skills in English. Nice to Have: Experience with Big Data technologies, such as Spark (and PySpark); Experience with SQL and exposure to ETL development. Benefits We believe in rewarding talent and dedication. Here's what you can expect as part of our team: Competitive full-time salary; Private Health Coverage on the Company’s group program; Flexible Working Hours; Top-of-the-Line Tools; Professional Development: Benefit from language courses, specialized training, and continuous learning opportunities; Career Growth: Work with some of the most innovative and exciting specialists in the industry; Dynamic Work Environment: Thrive in a setting that offers challenging goals, autonomy, and mentoring, fostering both personal and company growth. If you want an exciting challenge, work with some of the coolest technologies, and enjoy your time doing it, then join us! Submit your detailed CV in English, quoting reference: ( AIML/11/26 ). You may also consider all our other open vacancies by visiting the career section of our website ( www.eurodyn.com ) and follow us on Twitter (@EURODYN_Careers) and LinkedIn. EUROPEAN DYNAMICS (ED) ( www.eurodyn.com ) is a leading European Software, Information, and Communication Technologies company, operating internationally (Athens, Brussels, Luxembourg, Copenhagen, Berlin, Stockholm, London, Nicosia, Valetta, Vienna, Den Haag, Hong Kong, etc.) The company employs over 1100 engineers, IT experts, and consultants (around 3% PhD, 41% MSc, and 54% BSc). We design and develop software applications using integrated, state-of-the-art technology. Our current IT projects have a value exceeding 300 million EURO. EUROPEAN DYNAMICS is a renowned supplier of IT services to European Union Institutions, international organizations, European Agencies, and national government Administrations in 40 countries and 4 continents. As part of our dedication to the diversity of our workforce, we are committed to Equal Employment Opportunity without regard for race, colour, national origin, ethnicity, gender, disability, sexual orientation, gender identity, or religion. EUROPEAN DYNAMICS (ED) adheres to the General Data Protection Regulation principles by applying its Privacy Policy as published at www.eurodyn.com/privacy . By submitting an application to this position and by sharing your personal data with ED, you acknowledge and accept its Policy and authorize ED to process your personal data for the purposes of the company's recruitment opportunities, in line with the Policy.

Location: Vancouver, Canada; United States Our client is hiring a Staff-level engineer to lead a highly specialized team building cutting-edge, high-throughput signal processing systems that turn raw satellite radar data into SAR imagery, deployed on the ground and potentially on board spacecraft. Fully remote from the US; optional relocation to Vancouver later. What you will do • Lead the definition, specification, technical risk management, integration, verification and validation of SAR processors, new and existing • Supervise interface control document development; ensure hardware and software components integrate into the larger ground or space segment • Coordinate trade-offs between theoretical algorithms and their implementation on the actual processor • Troubleshoot root causes of processing errors and artefacts in image products and find mitigations; optimize processing time toward near-real-time • Take part in mission design trade-off studies; mentor the team; advise senior management and new business pursuits What you need • Degree in Electrical Engineering, Engineering Physics, Math or Physics (or equivalent) • 12+ years in an engineering environment, including 5+ years on complex signal processing systems (radar, medical imaging, computer vision or similar) and 10+ years in a large product development or systems engineering environment • Solid grounding in high-speed, high-throughput data analysis and transmission design • MATLAB, Python or C++ • Clear communicator to technical, sales, executive and customer audiences • US citizen or permanent resident Nice to have : SAR remote sensing (system design, operation, exploitation, calibration); satellite SAR payload design and operations; FPGA or ASIC based system design; geospatial data.

Location: Limassol, Cyprus Workplace: remote Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. We are looking for a Principal Streaming Technology Expert will serve as the company's senior technical authority on streaming technologies, supporting complex technical assessments , technology risk analysis, deep technical research, and strategic decision-making. Job Responsibilities Complex Technical Analysis: Investigate complex technical questions related to products, architecture, protocols, and implementations. Develop evidence-based technical positions on complex matters. Work with internal stakeholders and external experts on complex technical assessments. Prepare technical reports, diagrams, comparisons, and supporting materials. Explain complex streaming technologies to both technical and non-technical audiences. Technology Landscape & Risk Research: Research technologies, standards, publications, implementations, and industry practices. Compare company solutions with existing industry approaches and implementations. Conduct technical risk analysis related to technologies, standards, and third-party solutions. 👈 Support technical due diligence and risk assessments for products and architectural decisions. Track important technology trends and developments across the streaming ecosystem. Maintain awareness of emerging technical risks affecting the company's technology strategy. Technology Research & Documentation: Perform deep technical research relevant to the company's streaming platform and products. Maintain documentation of architecture, protocols, data flows, algorithms, DRM, CDNs, and media pipelines. Create technical diagrams, implementation analyses, and historical technical records. Investigate third-party technologies, standards, open-source components, and commercial solutions. Maintain understanding of how company technology differs from existing technical approaches. Preserve institutional knowledge around key architectural and engineering decisions. Internal Technical Authority: Act as a streaming technology expert across engineering, product, executive, and cross-functional teams. Review major architectural decisions requiring additional technical assessment or risk analysis. Collaborate with senior engineers and architects on complex technical reviews. Independently analyze source code, specifications, standards, protocols, and production architectures. Provide independent technical judgment on complex or sensitive technology questions. You’ll thrive here if you have Deep hands-on knowledge of video/audio streaming architectures, protocols, codecs, CDNs, and related technologies. Ability to independently analyze complex technical systems, standards, implementations, and architecture. Strong communication skills and ability to explain complex technical topics to non-technical audiences. Native or near-native English proficiency. Also would be nice: Experience working with complex technical reviews involving US-based stakeholders. Experience preparing technical materials for external review or formal assessment. Conditions We know that great talent deserves great conditions, so here's what you can expect when joining us: Full remote work. Competitive compensation with a service contract. Transparent performance reviews twice a year, with bonus opportunities and salary adjustments. An annual allowance that you can use for home office improvements, sports activities, equipment upgrades, and more—tailor it to what benefits you most. Investment in your development: paid language courses, access to various learning platforms, and a mindfulness benefit, including psychological support with 50% coverage. Career growth in a fast-scaling project with opportunities to influence technical decisions. A culture of recognition: our peer reward program celebrates contributions from across the team.

Location: Bucharest 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 As a Software Engineer II, you will design, build, and improve reliable cloud services that power critical automation capabilities across the UiPath platform. You will work on backend systems that need to scale, perform consistently, integrate with other platform services, and support customers across cloud, on-premises, and hybrid environments. WHAT YOU'LL DO AT UIPATH - Design, develop, test, and maintain backend and cloud-native services used across the UiPath platform. - Build scalable, secure, reliable, and high-performing distributed systems, with a focus on long-term maintainability. - Work on technical challenges related to scalability, availability, performance, observability, incident prevention, and multi-environment deployments. - Collaborate with product managers, engineers, architects, and other teams to deliver solutions aligned with customer and platform needs. - Contribute to system design, technical planning, code reviews, automation, and engineering best practices. - Identify bottlenecks, production issues, technical debt, and improvement areas, and drive practical solutions with strong ownership. - Engage directly with customers on technical calls to diagnose and resolve issues end to end. WHAT YOU'LL BRING TO THE TEAM - 3+ years of software engineering experience, with strong backend development experience. - Hands-on experience with one or more modern programming languages such as C#, Java, Python, or Go. - Good understanding of distributed systems, microservices, APIs, cloud-native architecture, and system design. - Experience building production-grade services in cloud environments such as Azure, AWS, or GCP. - Good knowledge of containers, Kubernetes, CI/CD, monitoring, logging, and observability. - Strong understanding of data structures, algorithms, multithreading, asynchronous programming, and performance considerations. - Experience with relational and/or NoSQL databases, messaging systems, or event-driven architectures. - Ability to write clean, well-tested, maintainable code and contribute to strong engineering practices. - Interest in automation, AI, developer platforms, enterprise software, or large-scale cloud systems is a plus. - Knowledge of cloud networking, especially in Azure (for example VPN Gateway, Private Link and ExpressRoute), is a plus 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.

Задачи: — Build high-quality software products with attention to detail and craftsmanship. — Work on real-world projects that have measurable impact. — Collaborate closely within an engineering team focused on growth-oriented solutions. — Take ownership from concept through delivery ensuring robustness at every stage. Требования: — Mastery of C# — Strong computer science fundamentals including best practices, design principles, algorithms and data structures. — .NET Core proficiency — JavaScript/TypeScript expertise — Concurrency understanding.

Location: Germany (Remote) At thinkcell, we’re seeking bright, creative C++ Developers with a solid theoretical background. Whether you're a seasoned professional or a recent graduate in Computer Science, Physics, or Mathematics, what matters most is your problem-solving ability and C++ skills. At thinkcell, we combine deep technical challenges with a healthy work-life balance and a culture that values thoughtful engineering over rushed delivery. Ideal candidates have: Strong C++ programming skills (through education or experience) A background in Computer Science, Mathematics, or Physics A passion for elegant, efficient algorithms Ability to work independently and creative problem-solving approaches Good command of English (German not required) How You’ll Work You’ll collaborate closely with the team, without being stuck in recurring meetings. Your feature ships when you think it’s ready - no time pressure! We encourage contributions from anyone What We Offer Brilliant Team: Work with international colleagues with strong academic and professional experience Work–life balance: Flexible working hours and an environment that respects your time and focus. Stable Environment: Join a market leader with a reliable product. Competitive salary & Relocation Support to Berlin: Work remotely from anywhere in Germany, while candidates based in Berlin are expected to work on-site. Guaranteed raise to 130k EUR after the first year Our Values As part of our team, you will embody and help shape the following principles that define us: Forward Thinking : We embrace change and challenge the status quo. Ownership : We take pride in our work and learn from our mistakes. Customer First : We prioritize delivering lasting value. Unified Team : We foster collaboration, respect, and integrity. Strive for Excellence : We set ambitious goals and pursue quality. Why is thinkcell the right place for you? We empower over 1.3 million users across 35,000 companies, including top consulting firms and major global enterprises. With offices in Berlin, Denver, Boston, London, Tokyo, and Dubai, we’re a diverse team of over 210 people, committed to innovation and excellence. thinkcell is more than a job – it's a chance to be part of an innovative, inclusive team that values collaboration and growth. We encourage applicants from all backgrounds to apply. Together, we can shape the future of productivity software. We can’t wait to see what you’ll bring to the team!

Location: Amsterdam, Netherlands; Berlin, Germany; London, United Kingdom; Poland; Prague, Czech Republic; Tel Aviv, Israel; 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. The role Nebius Token Factory is looking for scientists who can turn frontier LLM and VLM inference bottlenecks into research questions, conduct rigorous experiments, and translate their findings into production capabilities. You will own focused research and optimization projects, write strong code, and produce prototypes, publications, and technical artifacts that engineers can build on. Your research will span quantization, distillation, speculative decoding, KV-cache optimization, and model/runtime co-optimization, alongside inference engines and distributed inference architectures. You will investigate how these approaches interact, evaluate their trade-offs across model quality, latency, throughput, memory footprint, and cost per token, and work with engineering teams to bring promising results into production. Your responsibilities Lead research projects in efficient LLM and VLM inference, from hypotheses and experiments through ablations, prototypes, and production handoff. Develop and evaluate methods spanning quantization, quantization-aware training (QAT), distillation, speculative decoding, KV-cache reuse, KV-cache compression, long-context inference, MoE routing, and model/runtime co-optimization. Build prototypes using PyTorch, Triton, CUDA-adjacent tooling, or inference-serving frameworks, and collaborate with MLEs and platform engineers to turn them into production components. Research LLM request routing and scheduling strategies, including cache-aware load balancing and prefill–decode disaggregation (PDD). Evaluate how queueing, KV-cache transfer, worker placement, and prefill/decode capacity allocation affect latency, throughput, and serving cost. Investigate multi-node inference for dense and mixture-of-experts models, including wide expert parallelism (WideEP). Study expert placement, load imbalance, and computation/communication trade-offs, and use the findings to guide model and system architecture choices. Develop rigorous evaluations covering quality, latency, throughput, numerical stability, memory footprint, tail latency, and cost per token. Compare serving architectures under consistent workload conditions and GPU budgets. Work with MLE, GPU kernel, backend infrastructure, product, and customer teams to select research priorities with measurable production impact. Share results through internal reports, technical blogs, papers, and open-source artifacts, and mentor engineers and scientists on experimental design, scientific rigor, and model/system trade-offs. Must-haves A PhD in computer science, machine learning, ML systems, computer systems, computer architecture, electrical engineering, applied mathematics, or a closely related discipline. A strong publication record or equivalent research artifacts in ML, ML systems, efficient inference, model compression, quantization, distillation, serving systems, or related areas. Strong Python and PyTorch implementation skills, with the ability to turn ideas into experiments and working prototypes. Deep knowledge of LLMs, VLMs, transformer inference, decoding algorithms, model compression, quantization, and production-serving trade-offs. Strong experimental design skills covering ablations, baselines, metrics, statistical reasoning, and failure analysis. Excellent written and verbal communication. Nice-to-haves First-author publications at venues such as NeurIPS, ICML, ICLR, MLSys, ACL, EMNLP, ASPLOS, OSDI, SOSP, ISCA, or HPCA. Experience deploying ML models or inference optimizations in production. Experience with vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo, FlashAttention, FlashInfer, Triton, CUDA, or PyTorch internals. Experience applying post-training, SFT, DPO, RLHF, RLAIF, preference optimization, or synthetic data generation to inference quality or efficiency. Open-source research artifacts, widely used benchmarks, technical blogs, or invited talks demonstrating contributions to efficient AI systems. Research or implementation experience in one or more areas of distributed inference system architecture, such as LLM request routing, PDD, multi-node serving, or MoE expert parallelism, including WideEP. 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: Kuala Lumpur, Malaysia About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance. Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution. Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. About the Role We are at an inflection point where AI is fundamentally reshaping what products can do and how users experience them. We're not just looking for a product manager — we're looking for a hybrid product builder who truly understands AI capabilities and can translate technical potential into real user value. You will lead end-to-end product design for LLM / Agent-powered applications — from zero to one — across domains including intelligent customer service, personalized recommendations, AI assistants, and automated workflows. You are the critical connector between user insights, AI technical capabilities, and business objectives: someone who can discuss RAG retrieval strategies and multi-agent orchestration with ML engineers, while clearly articulating product value and delivery roadmaps to business stakeholders. If you have genuine passion for AI-native products and the ability to define clear product direction amid ambiguity and rapid change, we'd love to build the next generation of AI applications together. Key Responsibilities End-to-End AI Product Lifecycle Management Own the full product lifecycle of AI applications — including intelligent chatbots, AI assistants, recommendation systems, and automated workflows — from requirements definition and product design through to launch and delivery. Produce high-quality PRDs, interaction flow diagrams, and acceptance criteria while driving cross-functional teams to execute efficiently. LLM / Agent Capability Productization Deeply engage in Agent product design, including task planning workflows, tool-calling strategies (Function Calling / MCP), context management mechanisms, multi-agent orchestration logic, and graceful failure/fallback handling. Translate underlying model capabilities into meaningful, perceivable user value. AI Evaluation Framework & Quality Standards Build Harness evaluation frameworks for AI products — designing test scenario sets, evaluation metric systems (accuracy, hallucination rate, task completion rate, etc.), and regression test case libraries. Independently assess AI capability boundaries and drive continuous model iteration and product quality improvement. Conversational Product Design & Knowledge Engineering Lead platform architecture planning for intelligent customer service and conversational assistant products, covering knowledge base structure design, dialogue flow and SOP design, corpus annotation and training strategy, intelligent reply generation, and case summarization. Leverage large-scale data analysis to continuously optimize conversation quality and issue resolution rates. Personalization Engines & Generative UI Products Collaborate deeply with ML and data teams to design recommendation strategies that deliver truly personalized, individualized user experiences. Define generative UI product requirements and drive growth in core business metrics including CTR, conversion rate, and user retention. Establish comprehensive attribution analysis frameworks for recommendation effectiveness. AI Capability Integration with Business Scenarios Develop a thorough understanding of business goals and user pain points. Proactively identify opportunities to apply AI technologies — including RAG, Prompt Engineering, and multimodal capabilities — to concrete use cases. Define clear product evolution roadmaps that balance technical feasibility, user experience, and commercial value. Cross-Functional Collaboration & AI-Native Product Culture Act as the product Owner in close collaboration with algorithm, engineering, data, design, operations, and business teams. Maintain a strong sense of ownership in a fast-moving AI-native environment, continuously track industry developments, and rapidly translate emerging AI capabilities into product innovation opportunities. Requirements Product Experience : 3+ years of product management experience, with at least 1 year of direct hands-on experience delivering AI application products, AIGC products, or Agent products. Must have fully shipped at least one AI-related feature module or standalone product. AI Technical Understanding : Deep understanding of the productization of mainstream AI technologies, including but not limited to: LLM Prompt Engineering, RAG (Retrieval-Augmented Generation) architecture, Agent fundamentals (tool calling / task planning / context window management), and conversational system design. Ability to independently evaluate the product feasibility of technical proposals. Evaluation & Data Capabilities : Proven ability to design AI product evaluation frameworks — independently defining evaluation metrics, building test case sets, and tracking product performance through data analysis. Familiarity with A/B experiment design and a strong data-driven decision-making mindset. Documentation & Communication Skills : Ability to write structured, logically rigorous PRDs, technical requirement documents, and flow diagrams. Excellent cross-functional communication skills with the ability to accurately bridge information between technical and business teams, eliminating information gaps. User Insight & Product Thinking : Sharp ability to translate ambiguous user needs into clearly defined product requirements. Skilled at finding the right product balance between AI capability boundaries and user expectations — avoiding both overpromising and underutilizing model capabilities. Learning Agility & Ownership Mindset : Sustained enthusiasm and capacity for continuous learning in a rapidly evolving AI landscape. Strong sense of ownership — able to proactively define problems, drive decisions, and take accountability for outcomes in highly ambiguous environments. Nice to Have Familiarity with cutting-edge AI engineering practices including MCP ( Model Context Protocol ), Function Calling, and multi-agent orchestration frameworks (e.g., LangChain / AutoGen / CrewAI), enabling deep technical dialogue with engineering teams. Experience with AI Harness / Eval / Benchmark platform product design or usage, with involvement in establishing and maintaining LLM evaluation systems. Background in Fintech / e-commerce / SaaS industries, with an understanding of the unique product design requirements for AI in high-concurrency, compliance-sensitive environments. Bilingual fluency in Chinese and English (spoken and written), with the ability to independently drive product collaboration and cross-cultural communication within international teams. Why Join Us At Bybit, we are committed to fostering a supportive and enriching work environment. Our benefits include: - Study Growth Fund: We support your professional development and continuous learning. - Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation. - Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world. - Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company. - Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.

Location: Remote (USA) Workplace: remote Arcadia is dedicated to happier, healthier days for all. We believe that there is a better healthcare world – one powered by data. Our platform transforms complex, diverse data into a unified foundation for health, helping organizations deliver better care, boost revenue, and lower costs.   We’re a team of fiercely driven individuals committed to making healthcare more sustainable—and we’re looking for passionate people to help us get there.   For more information, visit arcadia.io. Why This Role Is Important to Arcadia As our business grows, and as AI is improving, we need fewer, better building blocks: less per-team glue, more self-service capabilities every team builds on, so engineers spend their time on customers instead of plumbing. This is platform engineering at Arcadia. The role could just as well be titled Developer Platform, DevEx, DevProd, or SRE. Arcadia builds and operates the petabyte-size lakehouse, and the client-facing applications that run on Kubernetes. The role will span both, reporting directly to the engineering VP. What Success Looks Like Arcadia engineers and their agents rely on platform building blocks, from services and pipelines to databases, queues, and storage, that come wired in with logging, metrics, tracing, alerts, encryption, access controls, backups, and cost tags, with sensible defaults. Teams change their own pipelines, environments, alerts, and SLOs. When something breaks, the owning team sees it first, traces it to the change that caused it, and rolls it back themselves. They see their own delivery numbers and cloud spend, and act on them. Platform upgrades reach them as a merged pull request, not a checklist. Engineers take the paved road because it's the fastest way to production, and platform engineers spend their time building capabilities, not working tickets. What You'll Be Doing Push quality attributes into the platform, especially as AI increases the volume of changes: test and regression gates, progressive delivery and fast rollback, supply-chain and policy checks in the pipeline, and cost that's visible and attributable to the teams. Run the platform as a curated internal product : find what slows teams down, pick the few capabilities worth building, publish the roadmap, and measure adoption, delivery speed, stability, and developer satisfaction. Build software : self-service APIs, templates, and golden paths for CI/CD, environments, and observability, so teams get what they need without waiting on anyone. You write a meaningful share of the code. Carry migrations : track usage, automate instead of handing out checklists, push through the final 20%, and sunset. Manage the platform's stakeholders : say yes with compromises, say no without breaking trust, bring shadow platforms back onto the paved road, and make cost visible to the teams that generate it. Set the technical direction and evolve the platform, and coach Senior Engineers through design partnership and review. Keep building out our software "dark factory" on top of our internal agentic platform - we should be offloading more and more to it over time. What You'll Bring Both halves of platform engineering: a software engineer 's instinct for clean abstractions and APIs, and a systems engineer 's depth in cloud, Kubernetes, networking, and IaC. Reliability you've owned: SLOs, observability, on-call, and incident response. Customer empathy : you talk to the engineers you serve, tell a real need from a loud request, and retire what nobody uses. Big, long-running projects you've seen through: migrations pushed past the final 20%, platforms sunset on purpose, and the attention to detail both require. A clear philosophy on structuring infrastructure and delivery for security, velocity, and reliability, and the stories behind it. Current, hands-on production coding , the habit of figuring things out (research, spike, deliver), and relentless pragmatism about what's worth building. Drive to reduce toil for everyone through software. Ability to initiate and get stuff done org-wide . No healthcare background required. Would Love for You to Have Regulated -data experience (HIPAA, PHI, SOC 2 or HITRUST environments). A public voice through talks, writing, or open source. Experience turning an infrastructure or DevOps team into a product-minded platform team . Experience building platform support that scales : support tiers, office hours, docs, and developer advocacy. Experience making cloud and CI cost visible and actionable for the teams that generate it. What You'll Get The opportunity to own Arcadia's platform and to set its direction for years. Direct influence on how Arcadia's engineering org works on daily basis; your tooling, patterns, and standards become examples others build on. Remote-first across the US, with in-person hubs growing in Boston, DC, and NYC. A flexible culture with personality and heart , named a Built In 2026 Best Place to Work. Work that shows up in patients' lives . 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: 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 Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. The RL Scaling team works on how RL scales: what happens to throughput, stability, and learning efficiency as models get larger, episodes get longer, and compute grows by orders of magnitude, and what has to change in our algorithms and systems to keep getting returns from that scale. This role sits squarely across research and engineering. You'll develop next-generation architectures and RL algorithms, take them from a small-scale result to a frontier-scale run, and understand every place they behave differently along the way. You'll build the systems that set how fast the team can iterate: how many experiments, at what scale, and how quickly we can trust the results. And you'll work on Anthropic's largest and fastest RL runs, where the gap between a good idea and a working one is often a problem no one has solved yet. Key responsibilities Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale Own end-to-end performance of our largest RL runs, from research code down to the hardware Build performance and cost models for proposed architecture and algorithm changes, and use them to decide which ideas get scaled Investigate training dynamics at scale, including instabilities, divergence, and throughput regressions, and trace them to root cause Minimum qualifications Deep familiarity with modern transformer language models, including their architecture, training dynamics, and the behavior of large-scale optimization Hands-on experience training large models in a distributed setting, including the tradeoffs between data, tensor, and pipeline parallelism A track record of original technical work in ML training or systems, such as new methods, architectures, or optimizations, demonstrated through research, open-source, or production impact Ability to design rigorous experiments at scale, including baselines, ablations, and enough statistical care to trust a result that costs real compute Ability to reason quantitatively about the compute, memory, and communication costs of a model or algorithm Strong programming skills in Python and JAX or PyTorch, and comfort reading and changing code at every layer of the stack Preferred qualifications Research experience in reinforcement learning, optimization, or large-scale training, published or otherwise Experience developing RL algorithms for language models Experience with scaling laws or other quantitative models of training efficiency Experience designing or modifying transformer architectures beyond standard configurations Experience scaling training to large fleets of accelerators and debugging the problems that only appear at scale Deep understanding of numerics in large-scale training, including low-precision formats and sources of instability Familiarity with how GPU or TPU performance characteristics shape architecture and algorithm choices Experience with C++ or Rust Representative projects Characterize how a new RL algorithm's throughput and learning efficiency change from small models to frontier scale, and fix what breaks Develop a new attention variant, get it working at full scale, and measure how its quality and throughput compare to the baseline Prepare our next largest-ever RL run: find what breaks when model size, context length, and compute all grow at once, and fix it before launch Trace a loss instability that only appears past a certain scale to its root cause, and work out whether the fix belongs in the algorithm, the numerics, or the system Build a model that predicts the throughput and cost of a proposed architecture change before anyone writes the kernel 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: $500,000 — $850,000 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: Limassol Cyprus Workplace: OnSite ABOUT US Scorewarrior is a game developer and publisher based in Limassol, Cyprus. We are working on Total Battle — a cross-platform MMO 4X strategy game with a deep social system and extensive player interaction. We have 2 million monthly active players and continue to grow with the goal of becoming the #1 game in the genre. Our team consists of 200+ passionate, talented, self-driven, and continually developing professionals who love making high-quality games. ABOUT THE POSITION We are looking for a Senior Product Analyst to join our General Analytics team: the analytics lead, an analytics engineer and you. Product teams have their own analysts; we take the research questions they cannot answer on their own, and we own how analytics is done across the company. The core of the role is research: high-uncertainty product questions where the answer is the estimated effect of a specific factor, not a dashboard. Whether to extend the game's lifecycle, how to tell that a new giant feature works, how to run experiments on veteran players spread across hundreds of kingdoms. Alongside it you own the methodology: how experiments and effect estimates are done at Scorewarrior, and whether a number is good enough for a decision and useful to other analysts afterwards. It is a senior individual-contributor role: close work with the analytics lead, short cycles with game designers and product managers. Pilots of the infra components (experimentation platform, visualization system, AI analyst assistant, ELT) are driven by the analytics lead and the infrastructure itself by the data tech lead; you join as the customer, not the builder. Game industry experience is not required. WHAT YOU WILL BE DOING - Take high-uncertainty questions from product teams (Old Players, New Players, Quality of Life, Platform) from a vague question to a decision the team acts on. - Design and analyze experiments in non-standard setups: delayed treatment for veteran players, kingdom-level (cluster) tests, small samples, heavy-tailed revenue. Own variance reduction, outlier handling, permutation tests, MDE and power, reporting rules. - Estimate effects where a classic A/B test is impossible, using causal inference and quasi-experimental designs, and turn one-off solutions into methods other analysts reuse: reference documents, dbt data marts, Tableau dashboards. - Be the last check before the business acts on a number: the assumptions behind a metric, a test read-out or a pilot's output. - Use Python inside research when SQL is not enough: a graph algorithm over clan and kingdom networks, an optimization problem, a simulation. - Specify logging for features shipped by teams without their own analyst, and cover their ad-hoc questions. REQUIRED QUALIFICATIONS - Experience running research with high uncertainty end-to-end, from problem framing to a decision the team acted on. - Hands-on causal inference and quasi-experimental methods (difference-in-differences, synthetic control, matching or similar) on product questions: you can say what breaks an estimate and how you checked it. - Hands-on A/B test design and analysis, and the applied statistics behind it: distributions, power and MDE, variance reduction, heavy tails and outliers. - Strong SQL on an analytical data warehouse; ClickHouse is a plus. - Working Python for research: you can implement an algorithm or a statistical procedure that has no ready-made library call, and you understand what your code, or your AI assistant's code, does and whether it can work. No production services expected. - Clear, concise communication in writing and in person: you fix agreements, and you say so when a result cannot be trusted, including to the people who asked for it. - English at B1 or above. PREFERRED QUALIFICATIONS - Data science background alongside analytics: modeling, segmentation, validating assumptions with statistical tests. - Experience building or improving an experimentation platform, or setting methodology that other analysts followed. - Hands-on experience with dbt and Tableau. - Understanding of F2P economics, network effects, social or competitive systems; you play games and are ready to play Total Battle. WHAT WE OFFER - A team of professionals with a passion for gamedev and a drive to make Total Battle the #1 MMO 4X strategy game. - An excellent remuneration package, including a 13th salary. - Full relocation coverage for you and your family to Cyprus (Limassol). - A modern, sunny office close to the sea. - Private health insurance for you and your family members. - A monthly pre-school, school, and university allowance for employees' children. - Lunch compensation. - A sports and fitness allowance. - Company-funded personal development opportunities (professional and language courses, books, etc.). - Bonuses for outstanding results, years of service, marriage, and childbirth. - Friendly monthly office parties and epic annual offsite company birthday and Christmas celebrations.

Location: San Francisco APPLICATIONS CLOSED The general application portal has closed for 2026. We will reopen applications at some point in 2027. Thank you for your interest in Perplexity careers! Welcome! This is the general application portal for university students and recent graduates who wish to be considered for full-time Member of Technical Staff positions at Perplexity. Our elite new grad cohorts enjoy unparalleled mentorship, top-of-market compensation, and the chance to tackle some of the deepest, thorniest challenges in frontier intelligence https://www.perplexity.ai/hub/blog/category/research. NOTE: if you attend one of our focus schools listed below, please do not apply via this portal as it is infrequently monitored due to high volume. Apply instead via the school-specific application portal below to ensure your application receives priority attention. FOCUS SCHOOLS (UNITED STATES) - APPLICATION PORTALS Caltech https://pplx.ai/2026Caltech | Columbia https://pplx.ai/2026Columbia | Cornell https://pplx.ai/2026Cornell | CMU https://pplx.ai/2026CMU | Duke https://pplx.ai/2026Duke | Georgia Tech https://pplx.ai/2026GATech Harvard https://pplx.ai/2026Harvard | MIT https://pplx.ai/2026MIT | Michigan https://pplx.ai/2026Michigan | Northwestern https://pplx.ai/2026Northwestern | NYU https://pplx.ai/2026NYU | Penn https://pplx.ai/2026Penn Princeton https://pplx.ai/2026Princeton | Purdue https://pplx.ai/2026Purdue | Stanford https://pplx.ai/2026Stanford | UC Berkeley https://pplx.ai/2026Berkeley | UChicago https://pplx.ai/2026UChicago UCLA https://pplx.ai/2026UCLA | UIUC https://pplx.ai/2026UIUC | UNC Chapel Hill https://pplx.ai/2026UNC | UT Austin https://pplx.ai/2026UTAustin UWashington https://pplx.ai/2026UW | Yale https://pplx.ai/2026Yale FOCUS SCHOOLS (CANADA) - APPLICATION PORTALS McGill https://pplx.ai/2026McGill | UBC https://pplx.ai/2026UBC | UToronto https://pplx.ai/2026UToronto | Waterloo https://pplx.ai/2026Waterloo EARLY CAREER TALENT @ PERPLEXITY Perplexity believes that exceptionally talented individuals at any stage can thrive in our high-velocity, high-ownership culture. Our early career talent program revolves around: - Breadth: New grads at Perplexity work across the stack, from Perplexity's agent harnesses to our AI inference and training systems. Many of our most beloved features and most important systems were shipped by individuals fresh out of school. - Depth: New grads are entrusted (and expected) to dive deep into whatever problem domains you work on. Often, your work will require you to become a world expert in some problem space that few others in the world have encountered. - Mentorship & Growth: We keep the size of our entering new grad cohorts at well below 10% of our technical team. Each individual enjoys a rich network of mentors to help them grow, and our new grads have a track record of becoming some of Perplexity's most senior and prolific team members. - Recognition: We select for the best and we recognize them accordingly. We set our early career compensation to rise well above that of top tech companies and startups. Post-hire, we aggressively recognize and reward growth in role. - Mission: Perplexity is AI for people who expect more. Our mission is to build frontier intelligence for the world's most discerning users, and each contribution you make will directly advance that mission. ACADEMIC REQUIREMENTS If you're not applying from a focus school listed above, we typically require you to possess the following qualifications: 1. GPA of ≥3.92, averaged across all CS and Math classes; and 2. Grade of A or A+ in your school's upper-level algorithms course. Additional advanced coursework in areas such as systems, AI/ML, advanced math, and other rigorous subjects is highly welcome.   NON-QUALIFYING APPLICATIONS - EVIDENCE OF EXCEPTIONAL ABILITY While you're welcome to submit your application if you don't meet these criteria, we will be looking for other evidence of exceptional ability. You are encouraged to briefly describe this evidence in response to the "Anything Else" question at the bottom of the application form. NOTE ON FELLOWSHIP OPPORTUNITIES This portal accepts applications for full-time roles at Perplexity. Internship applications are not accepted via this portal. If you're interested in short-term opportunities with our team, you may instead be interested in the Perplexity Research Fellowship. The Fellowship has a separate application process detailed here https://pplx.ai/fellowship. Note that Fellowship applications are extremely competitive; in particular, we don't expect to admit any undergraduate students to the Fellowship before their final year of study.

Location: San Francisco APPLICATIONS CLOSED The general application portal has closed for 2026. We will reopen applications at some point in 2027. Thank you for your interest in Perplexity careers! Welcome! This is the general application portal for university students and recent graduates who wish to be considered for full-time Member of Technical Staff positions at Perplexity. Our elite new grad cohorts enjoy unparalleled mentorship, top-of-market compensation, and the chance to tackle some of the deepest, thorniest challenges in frontier intelligence https://www.perplexity.ai/hub/blog/category/research. NOTE: if you attend one of our focus schools listed below, please do not apply via this portal as it is infrequently monitored due to high volume. Apply instead via the school-specific application portal below to ensure your application receives priority attention. FOCUS SCHOOLS (UNITED STATES) - APPLICATION PORTALS Caltech https://pplx.ai/2026Caltech | Columbia https://pplx.ai/2026Columbia | Cornell https://pplx.ai/2026Cornell | CMU https://pplx.ai/2026CMU | Duke https://pplx.ai/2026Duke | Georgia Tech https://pplx.ai/2026GATech Harvard https://pplx.ai/2026Harvard | MIT https://pplx.ai/2026MIT | Michigan https://pplx.ai/2026Michigan | Northwestern https://pplx.ai/2026Northwestern | NYU https://pplx.ai/2026NYU | Penn https://pplx.ai/2026Penn Princeton https://pplx.ai/2026Princeton | Purdue https://pplx.ai/2026Purdue | Stanford https://pplx.ai/2026Stanford | UC Berkeley https://pplx.ai/2026Berkeley | UChicago https://pplx.ai/2026UChicago UCLA https://pplx.ai/2026UCLA | UIUC https://pplx.ai/2026UIUC | UNC Chapel Hill https://pplx.ai/2026UNC | UT Austin https://pplx.ai/2026UTAustin UWashington https://pplx.ai/2026UW | Yale https://pplx.ai/2026Yale FOCUS SCHOOLS (CANADA) - APPLICATION PORTALS McGill https://pplx.ai/2026McGill | UBC https://pplx.ai/2026UBC | UToronto https://pplx.ai/2026UToronto | Waterloo https://pplx.ai/2026Waterloo EARLY CAREER TALENT @ PERPLEXITY Perplexity believes that exceptionally talented individuals at any stage can thrive in our high-velocity, high-ownership culture. Our early career talent program revolves around: - Breadth: New grads at Perplexity work across the stack, from Perplexity's agent harnesses to our AI inference and training systems. Many of our most beloved features and most important systems were shipped by individuals fresh out of school. - Depth: New grads are entrusted (and expected) to dive deep into whatever problem domains you work on. Often, your work will require you to become a world expert in some problem space that few others in the world have encountered. - Mentorship & Growth: We keep the size of our entering new grad cohorts at well below 10% of our technical team. Each individual enjoys a rich network of mentors to help them grow, and our new grads have a track record of becoming some of Perplexity's most senior and prolific team members. - Recognition: We select for the best and we recognize them accordingly. We set our early career compensation to rise well above that of top tech companies and startups. Post-hire, we aggressively recognize and reward growth in role. - Mission: Perplexity is AI for people who expect more. Our mission is to build frontier intelligence for the world's most discerning users, and each contribution you make will directly advance that mission. ACADEMIC REQUIREMENTS If you're not applying from a focus school listed above, we typically require you to possess the following qualifications: 1. GPA of ≥3.92, averaged across all CS and Math classes; and 2. Grade of A or A+ in your school's upper-level algorithms course. Additional advanced coursework in areas such as systems, AI/ML, advanced math, and other rigorous subjects is highly welcome.   NON-QUALIFYING APPLICATIONS - EVIDENCE OF EXCEPTIONAL ABILITY While you're welcome to submit your application if you don't meet these criteria, we will be looking for other evidence of exceptional ability. You are encouraged to briefly describe this evidence in response to the "Anything Else" question at the bottom of the application form. NOTE ON FELLOWSHIP OPPORTUNITIES This portal accepts applications for full-time roles at Perplexity. Internship applications are not accepted via this portal. If you're interested in short-term opportunities with our team, you may instead be interested in the Perplexity Research Fellowship. The Fellowship has a separate application process detailed here https://pplx.ai/fellowship. Note that Fellowship applications are extremely competitive; in particular, we don't expect to admit any undergraduate students to the Fellowship before their final year of study.

Location: New York City, NY; San Francisco, CA; 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 Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators. The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Significant software engineering experience, particularly with distributed systems Results-oriented, with a bias towards flexibility and impact Willingness to pick up slack, even if it goes outside your job description Desire to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Preferred qualifications Experience with high-performance, large-scale distributed systems Experience implementing and deploying machine learning systems at scale Experience with load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure) Proficiency in Python or Rust Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users reliably Contributing to new inference features Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers 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: $320,000 — $485,000 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: Andorra la Vella, Andorra; Buenos Aires, Argentina; Brasilia, Brazil; Rio de Janeiro, Brazil; Barcelona, Spain; Madrid, Spain; Milano, Italy; Rome, Italy; Abu Dhabi, United Arab Emirates; London, United Kingdom; Lugano, Switzerland; Warsaw, Poland; Amsterdam, Netherlands; Lisbon, Portugal; Dublin, Ireland; Bucharest, Romania; Bangalore, India; Kuala Lumpur, Malaysia Workplace: remote Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio. We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios. Responsibilities Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint. Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms. Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions. Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems. Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements. A degree in Computer Science  or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch. Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms. A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios. Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required. Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency. Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters. Deep understanding of the math and structure behind Diffusion Models and Vision Transformers Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc. Important information for candidates Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles: Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/ Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website. Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms. Double-check email addresses. All communication from us will come from emails ending in @ tether.to or @ tether.io We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately. When in doubt, feel free to reach out through our official website.

Location: United States Our client is hiring a SAR Payload Systems Engineer to support current and next-generation Earth-observation satellites. You will own the definition, design, integration, verification and sustainment of SAR payload subsystems across several satellite programs and act as the technical interface with customers, primes and internal teams. Fully remote from the US is now accepted. What you will do • Gather and trace payload requirements from mission level down to subsystem level • Design the SAR payload architecture: antenna arrays and RF front-end Tx/Rx, digital beamforming, processing chain and digital electronics, power, thermal, mass • Lead conceptual, preliminary and detailed design with trade studies and performance budgets; produce ICDs; specify hardware and review schematics and layouts • Performance simulations for tolerance budgeting and image quality; support SAR and moving-target-indication algorithm development; payload DC power budget; FMECA, fault tree, FDIR, reliability • Build the payload verification master plan (unit, subsystem, payload, environmental and EMC tests); lead test automation and reporting • Support mission operations: payload health monitoring, on-orbit anomaly root cause, telemetry analysis, operator training What you need • Degree in Electrical Engineering, Computer Science or Physics with 5+ years supporting remote sensing system development, integration and test on LEO/MEO missions • Strong technical writing (requirements, ICDs, test procedures, risk reports) and presentation skills • Hands-on systems integration and test experience; Confluence and JIRA • Works well with little supervision; strong written and spoken English (French an asset) • US citizen or permanent resident

Location: United States Our client is hiring a Staff-level engineer to lead a highly specialized team building cutting-edge, high-throughput signal processing systems that turn raw satellite radar data into SAR imagery, deployed on the ground and potentially on board spacecraft. Fully remote from the US; optional relocation to Vancouver later. What you will do • Lead the definition, specification, technical risk management, integration, verification and validation of SAR processors, new and existing • Supervise interface control document development; ensure hardware and software components integrate into the larger ground or space segment • Coordinate trade-offs between theoretical algorithms and their implementation on the actual processor • Troubleshoot root causes of processing errors and artefacts in image products and find mitigations; optimize processing time toward near-real-time • Take part in mission design trade-off studies; mentor the team; advise senior management and new business pursuits What you need • Degree in Electrical Engineering, Engineering Physics, Math or Physics (or equivalent) • 12+ years in an engineering environment, including 5+ years on complex signal processing systems (radar, medical imaging, computer vision or similar) and 10+ years in a large product development or systems engineering environment • Solid grounding in high-speed, high-throughput data analysis and transmission design • MATLAB, Python or C++ • Clear communicator to technical, sales, executive and customer audiences • US citizen or permanent resident Nice to have : SAR remote sensing (system design, operation, exploitation, calibration); satellite SAR payload design and operations; FPGA or ASIC based system design; geospatial data.

Location: Paris; Zurich; Warsaw; London 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. ABOUT THE RESEARCH ENGINEERING TEAM   The team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the research↔production spectrum as needs or interests evolve.   As a Research Engineer – ML track, you’ll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you’ll either join:   - Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or - Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, Safety …) and turn fresh ideas into repeatable, scalable code.     What You Will Do   • Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools. • Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs. • Design, implement and benchmark ML algorithms; write clear, efficient code in Python. • Deliver prototypes that become production-grade components for Vibe and our enterprise API.   What We're Looking For   • Master’s or PhD in Computer Science (or equivalent proven track record). • 4 + years working on large-scale ML codebases. • Hands-on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed / FSDP / SLURM / K8s). • Experience in deep learning, NLP or LLMs; bonus for CUDA or data-pipeline chops. • Strong software-design instincts: testing, code review, CI/CD. • Self-starter, low-ego, collaborative.   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.