Вакансии

Location: Paris; Zurich; Madrid; Amsterdam; Warsaw; Linz; Munich; London; Berlin Workplace: Remote 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 TEAM Mistral is building a sovereign AI cloud for Europe. Our customers in finance, healthcare, and the public sector run frontier models on European-jurisdiction infrastructure, and the Cloud Platform team builds the systems that make that possible — compute orchestration, Kubernetes, bare metal, storage, networking, and the datacenter fleet that runs it all. We run it all on our own metal, our own network, our own datacenters — which means when something breaks, the fix is ours to write. European Compute Units let enterprises commit to multi-year capacity on that infrastructure, and we are scaling toward a gigawatt of compute across Europe by 2030. You will design and ship the layer every sovereign AI deployment depends on and shape the team building it. THE ROLE This is a people-leadership role from day one. You will manage the team — hiring, coaching, performance, growth paths, honest feedback — while staying close to the code: roughly half your time in architecture decisions and the hardest technical problems the team faces, the other half leading your squad. If you are looking for a senior IC role, this is not it. AI agents don't run in browsers. They run in sandboxes — and you will lead the team building ours. We build secure, isolated, network-controlled environments with snapshotting primitives, designed for AI agents and reinforcement-learning workloads. An RL training run doesn't need one environment; it needs thousands, created and destroyed every second. An agent needs to be sandboxed from the world while still feeling fast enough to be useful. That tension — airtight isolation, at fleet scale, at low latency — is the product. Your customers are the people building the next generation of AI software on our infrastructure; the primitives you ship become the runtime their agents live in. WHAT YOU WILL DO - Build the isolation layer: microVMs or containers, namespaces, cgroups, seccomp, snapshot and restore. - Own the security boundary. Customers run code they didn't write and can't fully trust — your systems make that safe. - Scale to fleets: creation latency, density, and lifecycle management for thousands of concurrent environments. - Write Go alongside your team and own the architecture and the hardest implementation decisions. - Grow the engineers, not just the software — set the standard for ownership and coach people past their comfort zone. - Own people management for the team: hiring, performance, growth paths, and honest feedback. - Partner with Product Managers to turn frontier research needs into shippable primitives. WHAT WE'RE LOOKING FOR - 2+ years of real people leadership. You have managed engineers — hired, coached, given honest feedback, and grown them. Hands-on contribution matters here, but this role is judged on the team you build and lead, not just the code you write. - Deep Linux internals: namespaces, cgroups, seccomp, virtualization — ideally microVMs of the Firecracker class. - You have shipped production systems in Go. Not dabbled. Shipped. - You understand network isolation at the packet level — not just firewall rules. - Performance instincts: you know what a syscall costs, and you have the profiles to prove you've cared. - 8+ years building backend or infrastructure systems. - You have partnered with product, design, and business teams to ship software that reached real users. - A low-ego, team-first mindset. We care less about your exact domain and more about whether you are the kind of technical force other engineers want to work alongside. 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: Belgrade; London; Berlin Workplace: Hybrid Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. RESPONSIBILITIES - Push search and agent quality forward through improvements to models, training data, tools, and system design. - Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. - Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. - Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. - Improve retrieval and ranking models and the search interfaces agents use to find and assess information. - Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. - Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. - Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. QUALIFICATIONS - A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. - Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. - Experience designing rigorous evaluations, diagnosing failures, and translating experimental results into practical improvements. - Comfort with open-ended problems that require both research judgment and hands-on engineering. - A strong sense of ownership, curiosity, and the drive to carry an idea through to a working system. NICE TO HAVE - Experience with training models to use tools or complete tasks over many steps. - Multi-agent training, coordination, or evaluation. - Building agent harnesses, distributed training systems, or scalable inference infrastructure. - Large-scale retrieval, ranking, or recommendation systems.

Location: Paris 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. ABOUT THE ROLE We are hiring an LLM Scientist to push the boundaries of AI-driven scientific discovery. You will specialize in developing and optimizing large language models (LLMs), agentic AI, and deep learning frameworks to solve open problems in the natural sciences: Biology, Chemistry, Physics, and/or Materials Science. Your work will empower scientists with cutting-edge AI tools and accelerate research through: - Model-centric innovation: Improving LLMs’ capabilities to tackle complex scientific problems (e.g., literature synthesis, autonomous experimentation, rigorous derivations). - Cross-disciplinary collaboration: Partnering with Natural sciences domain experts to translate AI advancements into real-world scientific impact. WHAT YOU WILL DO - AI/ML Research: Participate in end-to-end training of LLM-based solutions, with a focus on scalability, generalization, and scientific applicability. - Data creation: Design original workflows to accumulate high quality scientific data at scale, either through synthetic or crowd sourced pipelines. - Algorithm Design: Use and improve reinforcement learning, or agentic systems tailored to Natural sciences challenges (e.g., modeling resolution, material property prediction, advanced data analysis and coding). - Interdisciplinary Bridge: Work closely with domain scientists to identify AI opportunities and refine models based on feedback. - Tooling & Infrastructure: Contribute to company infrastructure to improve usability for model training in scientific contexts and open-source AI tools for science for non-AI experts. - Autonomous Innovation: Set a research agenda for AI in science, exploring high-risk/high-reward ideas.   WHAT WE'RE ARE LOOKING FOR - AI/ML Expertise: Strong background in LLMs, deep learning, or agentic AI, with a track record of applying these to real-world problems (publications, open-source contributions, or deployed systems) – at the minimum extensive experience in computer science and ideally experience scaling synthetic data generation. - State-of-the-art Knowledge: Familiarity with the latest advancements in LLM architectures and post training. - Technical Depth: Hands-on experience with PyTorch/TensorFlow/JAX, model optimization, and scaling techniques (e.g., fine-tuning, RLHF). - Scientific Capability: Ability to understand 1 Natural Science domain at a high level (e.g., graduate level specialization + general undergrad knowledge) to design effective AI solutions. - Engineering Rigor: Proficiency in scientific computing (e.g., numerical methods, HPC) and software best practices. - Collaboration: Experience translating technical AI concepts for non-experts (e.g., scientists, engineers) and iterating based on user needs. - Mindset: Low ego, team player, and eager to tackle operational challenges (e.g., data pipelines, model deployment). MOTIVATIONAL PARAGRAPH When applying for the AI for Science team at Mistral, please describe in a short paragraph a potential project that you would like to contribute to the team, why it is challenging and interesting in general, and more specifically for Mistral. Please also highlight the specific skill set that you can bring to the team. 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: London, United Kingdom - Deliveroo Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Senior Software Engineer, GenAI Platform About the Team Deliveroo's GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalisation to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. About the Role You will join a small, high-leverage team building production infrastructure for Generative AI at Deliveroo and DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. You’re excited about this opportunity because you will… Lead the design of infrastructure that helps teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. Own and evolve our open-weights serving stack — real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) — alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution. Architect scalable, high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning that power real customer and internal automation use cases Push the cost and latency frontier of GPU inference — turning batch jobs that took days into hours and cutting inference cost by multiples — while giving product teams a clean choice across open-weight and closed-source models with reliability, fallback, observability, and cost controls built in. Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence. Partner closely with — and raise the technical bar for — ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives. Set technical direction for the future of the company's centralised GenAI platform — including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimisation, and other post-training and agentic techniques — enabling the next generation of AI-powered products, agents, automation, and personalisation. We’re excited about you because… BSc, MSc or PhD in Computer Science or equivalent 5+ years of industry experience in software engineering Deep backend engineering fundamentals, especially in Python and distributed systems. Track record of designing and owning production services, APIs, data pipelines, or ML infrastructure at scale. Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization. Deep hands-on experience with LLM inference and/or fine-tuning of open-weight models in production — serving (latency, throughput, batching, autoscaling, GPU utilization) and/or fine-tuning (SFT/DPO/LoRA). Demonstrated technical leadership: leading design across ambiguous, fast-moving technical areas, mentoring engineers, and turning customer use cases into reusable platform capabilities Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Nice To Haves Experience with LLM inference engines and serving frameworks (e.g., vLLM, SGLang, TensorRT-LLM) in production Experience with distributed/multi-node fine-tuning and training pipelines (SFT, DPO/RLHF, LoRA), including data preparation and evaluation GPU performance work — multi-node/distributed inference, KV-cache/memory optimisation, quantisation (FP8/INT8/AWQ/GPTQ), or cold-start/throughput tuning Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, serverless/elastic GPU platforms (e.g., Modal), or high-throughput batch systems Experience with LLM gateways, model routing, vendor abstraction, or cost attribution Experience building developer platforms, internal platforms, or self-serve infrastructure Experience building and deploying AI agents or MCP servers in production Experience with eval systems, LLM observability, tracing, RAG, search, or vector databases Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: San Francisco, CA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. Sierra’s Applied Research team advances the quality, speed, and cost efficiency of the models powering our agents across a wide range of tasks. Our work spans post-training open-weight models for specialized capabilities and pioneering new approaches to voice AI, turning research breakthroughs into reliable production systems. WHAT YOU’LL DO - Tackle unsolved applied AI and ML problems. Pushing the boundaries of post-training, voice AI, and long-horizon task execution, building agents that can reason, adapt, and reliably carry out complex tasks for customers. - Determine when to build specialized models and when to use externally provided frontier intelligence, balancing quality, speed, and cost to deliver customer value. - Turn ambiguous product and customer problems into well-framed machine learning problems. - Develop, fine-tune, evaluate, and deploy models that improve Sierra’s customer-facing AI agents. - Advance our post-training work, from supervised fine-tuning toward reinforcement learning and long-horizon optimization. - Build rigorous evaluations that connect model performance to real-world agent quality. - Work with large-scale, proprietary datasets spanning text and audio interactions. - Collaborate across Sierra while taking ideas from experimentation through production deployment and customer impact. WHAT YOU’LL BRING - Strong experience building and deploying production machine learning and AI systems. We welcome backgrounds across applied ML, including search, ranking, recommendations, advertising, language, and speech. - Excellent judgment in framing product problems as ML tasks and selecting the simplest & most effective approach. - Experience working deeply with data, experimentation, evaluation, and model iteration. - A practical, evidence-driven approach to ML, with strong judgement around when a problem calls for modeling and when a simpler solution will deliver the best outcome. - The ability to operate with high agency and work across the stack when needed to deliver an outcome. - Alignment with Sierra’s values, including Craftsmanship, Customer Obsession, and Competitive Intensity. - A degree in computer science, machine learning, or a related field, or equivalent professional experience. EVEN BETTER… - Experience with supervised fine-tuning or reinforcement learning. - Experience in search, ranking, recommendations, or advertising systems. - Experience training and deploying language, speech, or multimodal models. - Experience designing model evaluations tied to real-world product outcomes. - Experience working with large-scale consumer datasets or high-volume ML products. - Contributions to applied ML research or benchmarks. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: Renton, Washington, United States We take play seriously. We’re looking for curious adventurers ready to find their party, fueled by imagination and drive to build what’s never been built before. At Hasbro and Wizards of the Coast, you’ll collaborate with passionate teams to reimagine our iconic brands and create experiences that spark joy, connection, and community through the magic of play. This is your chance to shape legendary play that lasts a lifetime. This is a unique opportunity to help build the future of learning at Hasbro, creating a development ecosystem that strengthens leadership, accelerates business-critical capabilities, and delivers learning experiences that are distinctly Hasbro. The Director of Learning & Career Development will lead the design, development, and delivery of learning experiences that help our people grow and our business succeed. From onboarding and manager excellence to leadership development, workforce capability building, and differentiated talent programs, this leader will shape the learning experiences that support employees throughout their careers at Hasbro. This is a highly visible role that requires strategic thinking, sound judgment, and hands-on execution. The ideal candidate is a builder who can create a roadmap, earn alignment, develop a team, roll up their sleeves, and bring programs to life. They are equally comfortable facilitating a leadership session, designing a new program, partnering with senior leaders, or leveraging technology and AI to scale impact across a global workforce. A Day in the Life: Design & Execute Learning Strategy: Develop and evolve Hasbro's learning and career development roadmap, applying sound judgment to prioritize where we invest so learning supports business priorities, workforce needs, and employee growth. Partner Across the Business: Collaborate as a true team player with leaders, HR partners, and employees globally to assess capability needs, identify development opportunities, and create solutions that help teams and individuals perform at their best. Build & Deliver Learning Programs: Lead the design, development, facilitation, and delivery of high-impact learning experiences including onboarding, early career programs, manager excellence, leadership development, mentorship, coaching, and differentiated talent initiatives. Create Signature Hasbro Learning Experiences: Build distinctive, Hasbro-curated development experiences that strengthen culture, reinforce what great looks like at Hasbro, and help attract, engage, and retain top talent. Leverage internal expertise, executive involvement, business acumen, and the creativity of our brands to create learning experiences employees cannot get anywhere else. Build Critical Workforce Capabilities: Partner with business leaders to identify emerging skill needs and design scalable solutions that strengthen key capabilities such as AI, digital fluency, business acumen, leadership, and other enterprise priorities. Leverage Technology & AI to Scale Impact: Champion innovative learning technologies, AI-enabled tools, and emerging delivery methods that create engaging learning experiences, improve personalization, and extend the reach of a lean team. Continuously explore new approaches to learning and capability building. Activate Leaders as Teachers: Partner with executives and leaders to serve as teachers, mentors, coaches, and champions for learning across the organization. Integrate Learning with Talent, Culture & Inclusion: Collaborate across HR and business teams to embed learning into talent management, leadership expectations, performance practices, engagement, succession planning, and belonging initiatives. Measure & Communicate Impact: Apply critical thinking to data, insights, learner feedback, and business outcomes to evaluate effectiveness, demonstrate impact, and continuously improve programs. Build a High-Impact Learning Function: Lead, coach, and develop a small, agile team while creating scalable operating models, strong partnerships, and sustainable processes that maximize impact globally. Balance strategic leadership with hands-on ownership of program design, development, facilitation, and execution. What You'll Bring 10+ years of progressive experience in Learning & Development coupled with Talent Management, Leadership Development, Organizational Development, or related HR disciplines. Demonstrated success building and scaling learning programs and capabilities in complex, matrixed, and global organizations. Experience managing a team of direct reports is required, with a demonstrated ability to coach, mentor, and support their career development through meaningful feedback, development planning, and opportunities for growth Experience balancing strategic leadership with hands-on program design, content creation, facilitation, implementation, and execution. Strong understanding of the broader talent ecosystem, including performance management, talent development, succession planning, employee engagement, and organizational effectiveness. Proven ability to build trusted partnerships and influence leaders, HR partners, and stakeholders across functions, geographies, and cultures. Experience maximizing impact through lean teams, technology, innovative delivery models, and strategic vendor partnerships. Curiosity and enthusiasm for new technologies, evolving learning mediums, and innovative ways of building capability at scale. Strong data fluency, with the ability to define success measures, evaluate outcomes, and continuously improve programs. Experience engaging executives and senior leaders as active sponsors, teachers, coaches, and champions of development. Bonus: coaching certification; experience in manager excellence, leadership development, workforce capability building, talent acceleration, or early career programs. The pay transparency range for this role is listed below. The hiring range will vary based on factors such as experience, skills, location and market conditions. Additionally, employees may be eligible for annual and long-term incentives as part of their overall compensation package. Pay Range $150,500 — $240,800 USD Employees may be eligible for annual and long-term incentives as part of their overall compensation package, depending on role, location, and eligibility. Benefits and programs may include: Health & Wellness Time Off to Recharge Financial Well-being Life & Family Support Volunteer and Community Initiatives Learning & Development Exclusive Perks Please review our Applicant Privacy Notice to learn how we collect, use, and protect your personal information in connection with the application process.

Location: Zomba About GiveDirectly What if the most effective way to fight poverty was also the simplest: give people money and trust them to decide what they need? Since 2011, GiveDirectly has proven that idea at scale. We’ve delivered more than $1B in cash directly to 2+ million people living in poverty and crisis across 15 countries, and rigorous research shows the results: healthier kids, stronger businesses, sturdier homes, and more resilient families and local economies. Cash is now widely recognized as one of the most scalable, cost-effective, and dignified forms of aid. Our ambition goes beyond our own programs. We want cash to become the benchmark for aid, much as the index fund became the benchmark for investing, so that every aid dollar is held to one question: is this doing more good than giving the money directly to people living in poverty? We’re growing fast, and this is a rare and important moment to join. We expect to hit $1B in revenue in 2026 with significant growth forecast for 2027. At the same time we are building a new technology stack and operating model designed for a roughly 10x change in scale, and we are actively pursuing partnerships with major funders to move even more money in bigger ways, to people who need it. We are known for our extensive integration of technology into field processes; our quantitative approach to performance measurement; and our commitment to rigorous, independent, experimental evaluation of our impact, with multiple Randomized Control Trials completed and others in progress. How we work Our team spans 20+ countries and 69 languages. Our culture is candid, analytical, and non-hierarchical. We expect high ownership and give people real responsibility early. Our values are central to how we hire, work, and grow, and they are deliberately opinionated: Recipients first. Recipients’ preferences come before those of donors or ourselves. Team next. We optimize for organizational success, not individual success. Be proactively candid. We say what we believe and share information openly. Create positive energy. We aim to be a source of energy for colleagues, not a drain. Think rigorously; act quickly. We reason from first principles, then act rather than debate. Know yourself and grow. We own our imperfections and seek feedback to grow. Accept reality. Propose solutions. We focus on what can change and bring solutions, not just problems. Be productively ambitious. We take risks for step-change impact, not incremental progress. If they describe how you like to work and they energize you, this could be a great fit. Want to learn more? Read and listen: We are one of Time100’s Most Influential Companies of 2026, and our work has been covered by The Economist , NPR , TED , and The Washington Post . We're now preparing to deliver billions of dollars a year to people in extreme poverty, if funding allows. Read our CEO's essay on what that will take. Location: This role is based in  Zomba. The Safeguarding AFM is expected to spend significant time doing field visits in  Phalombe. About this role The Safeguarding Associate Field Manager ensures that GiveDirectly’s activities are planned and delivered in ways that prevent abuse. They also support appropriate and timely responses to safeguarding concerns. The role will primarily be based in the field, working closely with field staff and communities to identify and reduce safeguarding risks, promote safe behaviours, and strengthen confidence in our reporting pathways. The Safeguarding AFM supports the Safeguarding FM in contributing safeguarding input to operational decision making, guides effective case handling and escalation, and monitors and supports teams to apply best safeguarding practice consistently. This position upholds high safeguarding standards, reinforces trust, and ensures that all aspects of work protect the dignity and rights of recipients. Reports to: Safeguarding Field Manager Level : Associate Field Manager Travel Requirement: Regular travel required to conduct field visits in Phalombe What you’ll do: Direct engagement with communities, recipients, and staff in order to identify safeguarding risks and take early action to prevent abuse. Receive, document, and support responses to safeguarding concerns in line with our case management protocol by using survivor centred practice and established escalation pathways. Conduct Safeguarding investigations as needed, focusing on recipient/ field-based concerns. Support in developing and maintaining a network of safeguarding focal points to strengthen localised and collaborative risk identification and promote safeguarding best practice. Contribute safeguarding expertise to planning, design, and delivery to ensure that GiveDirectly’s activities remain safe, inclusive, and respectful. Support in delivering ongoing safeguarding training and sensitisation sessions for staff and partners, and support teams to apply best safeguarding practice consistently and promote safe behaviours. Represent safeguarding needs in field operations and maintain trusted relationships with local leaders, partners, and community actors. Monitor safeguarding trends and incidents, prepare self assessments and routine reports, and escalate and address gaps in safeguarding practices appropriately. What you’ll bring: Exceptional alignment with GiveDirectly Values and active demonstration of our core competencies: emotional intelligence, problem solving, project management, follow-through, and fostering inclusivity. We welcome and strongly encourage applications from candidates who have personal or professional experience in the low-income and/or historically marginalized communities that we serve. Language Requirement: Professional fluency in English and Chichewa. Minimum of 1-2 years experience in safeguarding, protection, community development, social work, or related operational roles, with a strong understanding of risks affecting development or humanitarian programmes. Strong judgement and the ability to take timely and appropriate action in sensitive or complex safeguarding situations. Confidence in identifying safeguarding risks across program activities and supporting staff to apply safe planning and safeguarding best practice consistently. Understanding of and commitment to survivor centred practice, confidentiality, and ethical decision making. Strong communication, facilitation, and documentation skills, including the ability to explain safeguarding obligations clearly and engage staff and community members respectfully. High levels of organisation, reliability, and attention to detail when maintaining safeguarding records, logs, and reports. Ability to work independently in field settings, manage competing priorities, and uphold safeguarding standards with professionalism and integrity. Working at GiveDirectly GiveDirectly is an Equal Opportunity Employer. All qualified applicants are considered for employment without regard to the person’s race, color, religion, national origin, sex, sexual orientation, age, marital status, veteran status, disability, or any other characteristic protected by applicable law. Flagging for US applicants: We invite you to " Know Your Rights " as an applicant. Commitment to Safeguarding As a global organization working with communities to eliminate extreme poverty, GiveDirectly takes the safeguarding of its recipients, staff, and partners seriously. To that end, GiveDirectly is a member of the Misconduct Disclosure Scheme , and will systematically check with previous employers about any abuse or misconduct related matters involving potential new hires. We may also employ other robust pre-hire screens, including in-depth reference checks, criminal background checks, and sanctions screens. These efforts help us continue to build and maintain trust with the communities we work with, and prevent abuse to our recipients and staff. **GD is committed to observing all local, national and international laws that protect people and basic human rights of all. GD is committed to a policy of “zero tolerance when it comes to preventing,  reporting, or responding to any form of abuse or  exploitation.” and expects anyone who works for GD to uphold the protection and safeguarding of our recipients as a priority.** Reasonable Accommodations We are committed to fostering an inclusive and accessible work environment. If you require any accommodations during the application or interview process, or to perform the essential functions of the role, please email us at careers@givedirectly.org with the email subject “Accommodation Needed”. We will work with you to ensure reasonable accommodations are made to support your needs. Want to put your best foot forward on your GiveDirectly application? Take a look at our Candidate Application Prep Guide ! Referrals Know the right person for this role? Please consider referring them . We offer a reward of $3,000 for a Senior Manager or above role, and $500 for a Manager role, paid if we end up hiring your referral. Thank you for sending great people our way!

Location: San Francisco, CA Workplace: Hybrid About Niantic Spatial AI has learned from almost everything online, but it still struggles with the physical world, where 99.5% of economic activity happens. It doesn’t know where things are, how spaces fit together, or what changes over time. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role Niantic Spatial makes the physical world computable, helping people and machines collaborate safely by aligning how they understand reality. One of the fundamental problems we're helping autonomy teams and engineers overcome is the sim-to-real gap for visual-spatial understanding. We're applying our team's decades of experience encoding the world precisely as it is at Google Maps, Google Earth, and Niantic Labs to build the scalable real-to-sim stack for embodied AI. We're looking for a Staff Engineer, Robot Learning to lead engineering for our real-to-sim product within the Embodied AI group. One of the fundamental problems facing autonomy teams is the sim-to-real gap in visual-spatial understanding, and we're applying decades of experience encoding the world precisely as it is to build the scalable real-to-sim stack for embodied AI. Working alongside the group's General Manager and Product leader, you'll inform the roadmap, own the technical requirements our researchers and engineers build against, and personally prototype and evaluate the changes you propose. You've lived the problems our customers are solving: you've trained and deployed embodied AI systems, seen where and why simulation fails to predict real-world performance, and worked through the consequences. This is not a role for someone who wants to manage and not ship, or someone who wants to ship without ownership of commercial consequences. This is a role for an entrepreneurial tech lead who loves to build and is energized by helping those around them do the best work of their lives. You have a co-founder mentality. You may have been part of a founding team before, or want to start your own business one day. What You'll Do - Sharpen the Roadmap - Bring first-hand knowledge of customer pain, existing solutions, and the value of doing better to roadmap decisions, and help focus effort on the most consequential problems to solve. - Own the Technical Requirements - Guide the team to design the real-to-sim stack pragmatically. Make the final recommendation on what to build, integrate, and simplify, ensuring capabilities work within customers' existing training and evaluation workflows. - Benchmark the Impact - Working with our Real-World Test Lab, design and run reproducible evaluations that measure the impact of our real-to-sim stack on policy transfer and real-world performance against customers' existing approaches. - Build and Ship - Lead engineering delivery and personally build critical features. Keep scope tight, remove blockers, and get performant capabilities into customers' hands quickly. - Raise the Technical Bar - Set a high bar for the team's work and deepen its understanding of robotics development and deployment, driving incremental improvement every week. What You'll Bring - Experience training, evaluating, and deploying robot policies in systems used by enterprise or government customers, with responsibility for performance in real operating conditions. - Deep practical experience using simulation for policy training or evaluation, including tools such as NVIDIA Isaac Sim, Isaac Lab, MuJoCo, or equivalent. You have diagnosed sim-to-real failures and understand when greater fidelity improves outcomes. - Hands-on experience with reinforcement learning, imitation learning, or both, and with deep-learning frameworks such as PyTorch. - A practical understanding of how visual perception and 3D scene representations affect robotics training, evaluation, and real-world performance. - Experience running experiments on real robots, from an ambiguous hypothesis through to defensible results. - Strong Python and C++ skills, with experience building reliable production software. - A bachelor's degree or higher in a relevant field. Nice to Have - You've authored or maintained a public robotics benchmark. - You've helped take an early product to repeatable adoption across multiple customers. - You've built or substantially extended robotics simulation infrastructure, including scene authoring, domain randomization, or large-scale training and evaluation. - You've trained and deployed vision-based navigation or mobility policies, particularly in varied, unstructured environments. - You've built pipelines that turn real-world reconstructions into simulation-ready environments. Competencies - Always Learning. Staying on top of the latest academic breakthroughs and commercial advancements, particularly in real-to-sim-to-real. - Relentless bias for action. You make decisions and ship as if the company’s success depends on it, because it does. You set the pace, and drive the people around you to rise to it. - Intellectually honest. You know there’s just one job that underpins every other in a startup: find the truth. You are relentless in your pursuit of it, including when it challenges your own convictions, and you raise concerns when you see them — even when it's uncomfortable, and especially when it's unpopular. - Pragmatic. You have no patience for not-invented-here syndrome and analysis paralysis. You find the fastest path to delivering customer value without going through one-way doors that undermine future scaling. - Confident and credible with customers. You can sit alongside an autonomy engineer and help them get to the root of their problems. You are comfortable speaking to customers and bring commercial nous to those discussions. Compensation & Benefits The expected salary range for this role is $270,000 – $300,000 per year. Compensation also includes an annual bonus, equity, and a comprehensive benefits package including medical, dental, and vision coverage, 401(k), and more. Location & Work Model This role is based in our San Francisco office, with three days per week in office. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed - you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

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: Large teams of agents are starting to solve problems no single agent can, from rewriting major codebases to formalizing landmark mathematics. Our team studies how these teams scale: what happens to performance, cost and coordination as the number of agents, the compute budget and the length of the task grow, and what has to change to keep getting returns from that scale. We build the platform and evaluations Anthropic uses to run and measure large agent teams, and other research teams build on them. This role lives at the boundary between research and engineering. It is a generalist role on a small team: you'll design and run large experiments, build the systems they run on, and get to the bottom of surprising results. We often need to go from a vague question to a running experiment quickly. Responsibilities: Design, run and interpret large-scale experiments on agent teams, reasoning rigorously about what the data does and doesn't show Investigate how performance and efficiency change as team size, compute and task horizon grow, and find the bottlenecks that limit them Build and scale the systems that run very large agent teams reliably, and debug the failures that only appear at scale Design evaluations for long-horizon problems, and keep their results trustworthy Build the tooling and metrics that let researchers see what a large agent team is doing and why Partner with research teams across Anthropic so they can run their own experiments on the platform, and communicate findings clearly You may be a good fit if you: Have significant software engineering, ML or research engineering experience Have owned something substantial end to end, such as a large system, an evaluation or benchmark, an agent product, or a research project Genuinely enjoy both research and engineering work Think quantitatively about complex systems, and think twice before trusting a number Can work from a vague question rather than a spec Are results-oriented, with a bias towards flexibility and impact Have clear written and verbal communication Care about the societal impacts of your work Strong candidates may also have: Experience building or operating large-scale distributed systems, such as schedulers, sandboxed code execution, or inference and RL infrastructure Built evaluations, benchmarks or harnesses for LLMs or agents Experience building complex agentic systems that use LLMs Experience with scaling laws or other large-scale empirical research A background in operations research, statistics, economics, physics, quantitative finance, or another field that models and optimizes complex systems Strong candidates need not have: Formal certifications or education credentials Academic research experience or publication history Prior experience with multi-agent systems or reinforcement learning Representative projects: Measure how performance scales with the number of agents on a hard problem, and explain where the curve bends and why Prepare our largest-ever agent run: find what breaks as team size and task length grow together, and fix it before launch Work out how to allocate a fixed compute budget across a team of agents to solve a problem fastest Build tooling that turns the activity of a large agent team into something a researcher can read in minutes Design a novel eval that distinguishes real gains in teamwork from artifacts of the evaluation setup 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. 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: 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 We're seeking a business development lead to own Anthropic's BD partnership footprint with a small number of the world's largest and most consequential technology companies. These are not single-threaded accounts. Each relationship spans many businesses at once — consumer products, devices and operating systems, productivity and collaboration software, cloud and developer platforms, commerce, and enterprise distribution. Your job is to see the whole board, decide where Anthropic should lean in and where it shouldn't, and turn that judgment into signed deals. The center of gravity for this role is product and distribution partnerships: co-developing opportunities with partners, and structuring the commercial, technical, and go-to-market terms that make those partnerships durable. You'll typically be running several deal streams inside the same partner in parallel — at different stages, with different counterparts, and with terms that interact with one another — and you'll be the person responsible for keeping them coherent. This is an individual contributor role for a seasoned dealmaker who is comfortable as the primary counterpart to senior executives at very large companies, who brings strong judgment to ambiguous, high-stakes situations, and who can carry a complex, multi-party negotiation from first conversation through signature and into execution. Key responsibilities Manage a small number of large, multi-faceted partner relationships end to end: set the strategy for each relationship, decide which opportunities to pursue and in what order, and stay accountable for the overall health and commercial output of the partnership across every surface it touches Lead product partnerships: identify and structure opportunities to embed Claude in partners' consumer and enterprise products, co-develop new products and features, and define the product, technical, data, and brand terms that come with them, working closely with Anthropic's product and engineering leaders Run multiple deal streams in parallel: manage several concurrent negotiations within the same partner — product integrations, distribution and go-to-market, commercial and consumption agreements, and infrastructure — and sequence and connect them so terms in one stream reinforce rather than undercut the others Negotiate complex, first-of-kind agreements: lead end-to-end negotiations involving novel commercial structures, revenue and economics sharing, product and roadmap commitments, exclusivity and competitive provisions, data terms, and multi-year, multi-component value exchanges Act as an executive counterpart: build and manage relationships with senior executives and their teams on the partner side, serve as Anthropic's primary voice into the partnership, and prepare and steer Anthropic's own executives through partner-level engagements Exercise judgment on behalf of Anthropic: weigh commercial upside against strategic, competitive, product, and mission considerations; know when to say no; and make clear, well-reasoned recommendations to Anthropic leadership on trade-offs that don't have a playbook Drive cross-functional execution: coordinate Product, Engineering, Sales, Marketing, Finance, Legal, and Policy across the life of a partnership, from initial structuring through negotiation, launch, and ongoing governance, ensuring what we sign is something Anthropic can deliver Minimum qualifications Direct experience owning a large, multi-business partner relationship, where you were responsible for the whole relationship rather than a single deal or product line Track record of structuring and closing product partnerships — embedding technology into partner products, co-developed products, distribution through partner surfaces, or similar — in addition to conventional commercial agreements Experience personally leading complex, multi-stakeholder negotiations with senior executives, including deals with interlocking terms, competitive sensitivities, and multi-year commitments Demonstrated ability to manage several significant negotiations at the same time without losing the thread on any of them Experience coordinating cross-functional execution (e.g., Product, Engineering, Legal, Finance) to bring a complex agreement from structuring through signature and delivery Preferred qualifications 10+ years in strategic business development, strategic partnerships, or corporate development at technology companies, with meaningful time spent managing relationships with very large technology partners Experience on either side of a partnership between a foundation model or AI platform provider and a large technology company Experience working inside one of the very large technology companies, with a practical understanding of how decisions get made, who holds budget and roadmap authority, and how to navigate them Experience with partnerships that span both consumer and enterprise businesses, or that combine product, distribution, and infrastructure components in a single relationship Understanding of foundation model capabilities and how they translate into partner products, with enough technical fluency to work credibly with product and engineering leaders on both sides Background in corporate development, strategy, or a legal or finance discipline involving structuring and papering unusually complex agreements 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: $300,000 — $365,000 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. 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: United States; Canada; United Kingdom; Germany; The Netherlands Workplace: Remote ClickHouse Labs is an applied research group that works closely with engineering teams to identify challenging problems in database systems and develop novel solutions. Our goal is to advance the state of the art and translate research ideas into real-world system improvements. ABOUT THE ROLE As a Research Scientist at ClickHouse Labs, you will work on high-impact problems at the intersection of database systems, distributed systems, AI, and systems software engineering while collaborating with experienced researchers and engineers. The role covers a broad range of problems across database systems research and engineering, including but not limited to query optimization, execution engines, distributed systems, consensus protocols, materialized views, indexing and data structures, benchmarking, workload analysis, and emerging agentic workloads. In this role, you will work on leading open-source database systems (e.g., ClickHouse, PostgreSQL). You will investigate performance and scalability bottlenecks in production-quality systems, develop new algorithms and system designs, and evaluate them under realistic workloads and hardware configurations. Projects may involve improving query planning and execution, reducing CPU and memory overhead, increasing throughput and concurrency, scaling across distributed deployments, or redesigning system components to leverage modern hardware better. You will work closely with engineers to turn successful ideas into robust implementations that can be deployed and maintained in widely used open-source systems. Researchers are encouraged to publish their work, contribute to open-source projects, participate in leading research conferences, and pursue ambitious projects with strong engineering and research support. RESPONSIBILITIES - Conduct applied research aimed at advancing the performance, scalability, reliability, and functionality of open-source database management systems, including ClickHouse and PostgreSQL. - Design and evaluate new algorithms, data structures, and system architectures for areas such as query optimization, indexing, storage management, query execution, and distributed data management. - Develop high-quality research prototypes and production-grade implementations, and work with engineering teams to integrate successful techniques into open-source and production systems. - Collaborate closely with database engine, infrastructure, and data-plane engineers to identify high-impact research problems and translate research results into practical system improvements. - Analyze large-scale database workloads, performance traces, benchmarks, and production telemetry to identify bottlenecks and optimization opportunities. - Design rigorous experiments and benchmarks to evaluate new techniques across realistic workloads, hardware configurations, and deployment environments. - Communicate research results through technical reports, open-source contributions, internal presentations, and publications at leading database and systems venues (e.g., SIGMOD, VLDB, CIDR). - Contribute to the broader technical direction of ClickHouse Labs by identifying emerging research opportunities and helping shape longer-term research projects. QUALIFICATIONS MINIMUM QUALIFICATIONS - Masters/Ph.D. in Computer Science, Data Science, or a related field, with research experience in databases, distributed systems, systems software, or machine learning systems. - Strong publication record in leading peer-reviewed research venues such as SIGMOD, VLDB, SOSP, OSDI, NSDI, or NeurIPS, with work relevant to databases or systems. - Strong programming and systems-development background, including experience working with database internals or other large systems codebases such as PostgreSQL, MySQL, ClickHouse, or comparable modern DBMSs. - Proficiency in systems programming using C, C++, Rust, Zig, or a comparable low-level programming language. - Strong analytical, experimental, problem-solving, and technical communication skills. PREFERRED QUALIFICATIONS - Experience developing or operating database systems in cloud environments such as AWS, Google Cloud Platform, or Microsoft Azure. - Familiarity with large language models, reinforcement learning, learned optimization, or other techniques at the intersection of machine learning and systems. - Experience contributing to large open-source systems projects, particularly database engines, distributed systems, compilers, or storage systems. BONUS QUALIFICATIONS - Familiarity with modern systems-development and verification tooling, including formal specification or model-checking frameworks such as TLA+/PlusCal, Alloy, or Lean, as well as relevant development tools and languages such as LLVM, eBPF, Python, Go, or advanced profiling and debugging tools (e.g., perf, sanitizers, or tracing frameworks). - Proven track record in optimizing database systems via hardware acceleration (e.g., GPU, FPGA, CXL), with a focus on designing methods for offloading for query execution, storage layers, and data-intensive primitives using frameworks like CUDA, SYCL, ROCm, or specialized FPGA development flows. PERKS - Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries. - Healthcare - Employer contributions towards your healthcare. - Equity in the company - Every new team member who joins our company receives stock options. - Time off - Flexible time off in the US, generous entitlement in other countries. - A USD$500 Home office setup if you’re a remote employee. - Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites. CULTURE - WE ALL SHAPE IT As part of a rapidly scaling start-up, you will be instrumental in shaping our culture. Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse. EQUAL OPPORTUNITY & PRIVACY ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.

Location: Berlin adjoe builds the technologies behind mobile app growth and monetization, challenging the status quo of adtech by redefining how apps acquire users and generate revenue. Our two products, Playtime Arcade and adjoe Ads, sit at opposite ends of the mobile advertising spectrum: rewarded engagement and programmatic in-app advertising. Together they run on 13% of the world’s smartphones, connecting advertisers, publishers, and hundreds of millions of users, with one goal: making mobile advertising work better for everyone in the ecosystem. Next-Gen Machine Intelligence for Auctions & Real-Time Bidding The Data Science Research team builds the foundational algorithms that govern real-time bidding, budget pacing, and allocation mechanics across our products. Operating as a horizontal deep-tech layer, the team leverages advanced AI—specifically reinforcement learning, objective-based optimization, and control theory—to deliver critical systems that perfectly harmonize advertiser ROI, platform health, and user relevance. These frameworks scale adjoe’s products beyond standard industry limitations, utilizing behavioral and transactional data from over 770 million users. The team operates at the intersection of high-load, low-latency engineering, auction mechanism design, and state-of-the-art machine learning. Acting as the company’s internal science bar raiser, they translate complex business constraints into mathematical objectives. The stack is optimized for high throughput: PyTorch for training deep learning and RL models, distributed architectures for large-scale Bayesian inference, Trino and Athena for querying massive user-behavior data lakes, and dedicated GPU infrastructure. The full lifecycle of these AI capabilities is owned by the team—from academic paper translation and offline prototyping to deploying core algorithmic frameworks built to sustain ultra-low latency, real-time production environments evaluating tens of thousands of requests per second. Your Mission & Who We Are Looking For: - PhD or equivalent research depth, with a production track record. You have a PhD in CS, Statistics, Math, or Physics (or an MSc with extensive industry research) and a track record of peer-reviewed publications in fields like Computational Advertising, Auction Theory, Mechanism Design, or Game Theory. You’ve spent 4+ years optimizing complex systems through automated algorithms in AdTech, marketplaces, or high-frequency trading. - You translate research into production, not just prototypes. You distill SOTA research into robust, production-ready code optimized for sub-millisecond latency. At adjoe, that means architecting sophisticated auction mechanics, real-time bidding engines, and allocation algorithms serving millions of requests across a stack built on 770 million users. - Deep expertise in Reinforcement Learning and Optimization. You have hands-on, deep theoretical and technical expertise in objective-based optimization, control theory, or RL applied specifically to bidding, pricing strategy, and budget pacing under extreme production constraints. - Mastering high-dimensional data at scale. Large-scale Bayesian inference and handling sparse, high-dimensional advertising data are core to your work. You are strongly proficient in Python and related stacks, and know exactly how to architect scalable data pipelines to feed real-time optimization models. - Raises the technical bar around them. You lead architectural debates, collaborate tightly with Product Managers and Engineers to map business goals to mathematical objective functions, mentor junior scientists, and drive the team’s research direction without needing a roadmap handed to you. 🌎 WE WELCOME APPLICATIONS FROM TALENT WORLDWIDE AND PROVIDE RELOCATION SUPPORT TO HAMBURG, GERMANY FOR THOSE READY TO JOIN OUR TEAM. What’s in It for You? At adjoe, you’re not here to just close JIRA tickets, you’re helping build the infrastructure behind one of the most impactful platforms in adtech. The systems you work on will reach hundreds of millions of users and power billions of decisions every day. - Go Big. Own projects with impact on 770M users and push adtech boundaries. - Move Fast. Ship solutions multiple times a day, learn from results, and keep momentum. - Be Direct. Solve problems openly and collaborate across teams. - Thrive Together. Grow with a diverse, global team of people from over 40 different countries that learn from each other. - Have Fun. Celebrate wins, enjoy daily victories, and bring your energy. We welcome applications from people who will contribute to the diversity of our company.

Location: West Palm Beach, Florida, United States Graham Capital Management, L.P. (collectively with its affiliates, "Graham") is an alternative investment manager founded in 1994 by Kenneth G. Tropin. Specializing in discretionary and quantitative macro strategies, Graham is dedicated to delivering strong, uncorrelated returns across a wide range of market environments. As one of the industry’s longest-standing global macro and trend-following managers, Graham remains committed to innovation, evolving its strategies through a robust investment, technology, and operational infrastructure. Graham harnesses the synergies between its discretionary and quantitative trading businesses to offer a broad suite of complementary alpha strategies, each built on the principles of thoughtful portfolio construction, active risk management, and diversification by design. Graham invests significant proprietary capital alongside its clients – including global institutions, endowments, foundations, family offices, sovereign wealth funds, investment management advisors, and qualified individual investors – reinforcing alignment of interests across all strategies. The foundation of Graham’s sustainability and success is the experience and contributions of its people. The firm seeks to cultivate talent, encourage the diversity of ideas, and respect the contributions of all. In turn, each employee shares in the responsibility of strengthening those around them. Description Graham is seeking a Quantitative Research Developer to join our Quantitative Strategies team. The individual will research and develop ways to improve Graham’s current trading code base and create new systematic trading signals to complement and diversify the firm’s main strategies. The individual will maximize performance and competitiveness by utilizing advanced methods in quantitative analysis and software development. Responsibilities Create production code for new trading signals Ensure the efficiency and accuracy of existing production code Research and develop methods to make existing trading signals more efficient, profitable and robust Research and develop new signals that trade futures and FX markets that complement and diversify production strategies in terms of style, source of alpha and markets traded Follow robust research and development procedures to reduce differences between simulated and actual performance Work collaboratively in a research team environment, using common development tools to facilitate robust implementation of research as well as production versions of trading systems Interact with other departments – technology, operations, trading, marketing, and accounting - to ensure current and proposed ideas are implemented, monitored and executed efficiently and accurately Regularly present findings and ideas to management and investment committee Complete other projects as requested by senior management Requirements PhD or MS in a quantitative field 2+ years related experience in systematic futures and/or FX trading on the buy side Exposure to securities and derivatives markets and investment processes with knowledge in mid-to-low frequency systematic strategies Advanced programming experience in languages suited for quantitative research and strategy implementation – python and/or MATLAB preferred Ability to synthesize complex topics into easily digestible written commentary Strong communication skills – both written and verbal This role requires commuting into our West Palm Beach, FL office Mondays through Fridays. Please note that our central Quantitative Research team sits out of Rowayton, CT but the manager for this new hire will be based out of West Palm Beach, FL. Base Salary Range The anticipated base salary range for this position is $200,000 to $275,000. The anticipated range is based on information as of the time this post was generated and does not include any discretionary bonus or benefits (see eligibility below). The applicable annual salary or hourly rate paid to a successful applicant will be determined based on multiple factors, including without limitation the nature and extent of prior experience, skills, and qualifications.  This wage range may be modified in the future. In addition, the employee who fills this role will be eligible for a discretionary annual bonus, as well as a wide array of benefit programs, such as medical and life insurance, 401(K) plans, and access to other healthcare programs. Notes: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, benefits, or any other form of compensation that a particular employee may be eligible for remains in the Company's sole discretion unless and until paid and may be modified at Graham’s sole discretion, consistent with the law. Other Graham is committed to providing equal employment opportunity to all employees and applicants for employment without regard to their race, color, religious creed, gender, age, national origin, ancestry, alienage, citizenship status, handicap, disability, marital status, sexual orientation, gender identity, pregnancy, childbirth or other related conditions, military status, genetic information, or any other personal characteristics protected by applicable law. This policy applies to all terms and conditions of employment, including hiring, placement, promotion, layoff, termination, transfer, leave of absence and compensation. Graham offers health benefits to eligible full-time U.S. employees, including medical, dental, vision, life and disability insurance, as well as other voluntary benefits such as spending accounts (HSA and FSA), and a profit contribution retirement plan.  All employees also receive paid vacation and sick leave.  Benefits eligibility is dependent upon a variety of factors, including employee classification and applicable waiting periods.  Benefits are subject to change and may differ for non-U.S. roles.

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 Every time Claude runs code, uses a computer, or works as an agent, it does so inside a sandbox. Our Sandboxing team builds the isolation layer behind that work. The same systems run the code Claude writes for users, the environments we train and evaluate models in, and the agents our customers deploy. These workloads are untrusted by design, and there are a lot of them. Sandboxes need to start in milliseconds, hold up under adversarial code, and scale to a very large number of concurrent sessions. You will work at the boundary between the Linux kernel, virtualization, and the container ecosystem. You will partner with research, product, and security teams to make sure that safe and fast do not trade off against each other. Key responsibilities Design, build, and operate the sandboxing infrastructure that runs untrusted, model-generated code and agent workloads at scale Improve sandbox startup time, density, and throughput, including snapshot and restore, checkpointing, and warm pools Strengthen isolation across compute, filesystem, and network, including egress controls and per-session credential handling Investigate and fix performance, reliability, and security issues at the kernel, hypervisor, and container runtime level Build the monitoring, tracing, and debugging tools that show where time and resources go inside a sandbox Work with researchers to support reinforcement learning environments and evaluations that need fast, reproducible, isolated execution Work with product and platform engineers to expose sandboxes as a dependable, well-designed capability for Claude products and customers Partner with security teams to threat-model the platform and to test, harden, and respond to escape and abuse scenarios Work with cloud providers on the hardware and platform features that our workloads depend on Share knowledge on systems programming and Linux internals, and help set technical standards for the team Minimum qualifications Software engineering experience in Linux systems programming, kernel development, or another low-level area Strong programming skills in at least one systems language such as Rust, C, C++, or Go Working knowledge of virtualization or container isolation technologies such as KVM, QEMU, Firecracker, gVisor, or runc Understanding of Linux resource management, including namespaces, cgroups, scheduling, and memory management Experience profiling and debugging performance issues at the system level Ability to work in unfamiliar codebases and technical areas, and to ship practical solutions with measurable results Strong communication skills and a commitment to building safe, reliable systems Preferred qualifications Experience building or operating a multi-tenant sandbox, serverless, or code execution platform Experience with microVMs, user-space kernels, or lightweight virtualization, including snapshot and restore Experience with OS-level security hardening, including seccomp, LSMs, and threat modeling of untrusted code Experience with eBPF and kernel tracing tools Experience with Kubernetes and cloud infrastructure at scale (AWS, GCP) Experience with network isolation, high-performance networking, or building egress proxies and policy layers Experience with sandboxes for AI agents, computer use, or reinforcement learning environments Experience with GPU virtualization, accelerators, or performance work on machine learning workloads Prior experience as a technical lead or mentor Representative projects Cutting sandbox cold start from seconds to milliseconds with snapshot-based restore and pre-warmed pools Designing a network egress policy layer so agents can reach approved services without exposing secrets Running many thousands of parallel reinforcement learning environments with strong isolation between them Building tracing tools that attribute latency and resource use inside a running sandbox Reducing per-sandbox memory overhead to raise density on each host Hardening the runtime against escape attempts found in internal red-team exercises 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. 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: Limerick At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Within Membership Services, we bring that mission to life by transforming every touchpoint into a catalyst for progress, so members feel equipped to rise to the moment, every moment. WHOOP is seeking a Change Management Specialist to help Membership Services successfully adopt, embed, and sustain operational change. This role will help shape and operate the team’s change management framework, supporting changes to products, policies, processes, tools, and ways of working. This includes change intake, impact assessment, sizing, governance, implementation planning, adoption measurement, and reinforcement. You will partner closely with Learning & Training, Quality, Knowledge Management, Support Operations, and Readiness to translate upcoming changes into coordinated, practical plans. You will help ensure Membership Services leaders and representatives understand what is changing, why it matters, how their work will be affected, and what support they need to confidently serve our members. Through structured planning, frontline engagement, data, and feedback, you will identify adoption risks, coordinate the right support, and help ensure changes are clearly understood, effectively implemented, and sustained over time - enabling Membership Services to consistently deliver the distinguished service our members expect. RESPONSIBILITIES - Manage the Membership Services change intake, assessment, and sizing process, evaluating the impact on both members and internal teams to determine the appropriate path. - Build and execute right-sized change plans that define the intended member experience, impacted audiences, communications, enablement needs, milestones, dependencies, risks, ownership, and success measures. - Coordinate with Learning & Training, Quality, Knowledge Management, and Support Operations to ensure representatives have the guidance, skills, processes, and resources needed to provide accurate and consistent member support. - Assess the impact of upcoming changes on AI-enabled support and automation, coordinating updates to knowledge, workflows, guardrails, testing, and escalation paths to ensure accurate and consistent member experiences from launch. - Manage assigned changes through implementation, adoption, and reinforcement, anticipating potential member friction and ensuring teams are prepared to support the experience from launch. - Partner with Launch Readiness Specialists on complex initiatives, leading or supporting the employee impact and adoption workstream while bringing frontline and member insights into readiness decisions. - Engage Membership Services leaders and frontline teams to validate impacts, identify adoption barriers, gather feedback, and ensure change plans reflect the realities of the member experience. - Track adoption and outcomes using employee feedback, training and knowledge indicators, quality trends, process adherence, operational performance, and member contact data; coordinate targeted action where gaps emerge. - Provide clear stakeholder updates, facilitate post-implementation reviews, and apply lessons learned to reduce member friction and continuously improve how change is delivered across Membership Services. QUALIFICATIONS - 2+ years of experience in change management, project coordination, enablement, operations, or a related field. - Experience supporting change from planning through implementation, adoption, and reinforcement. - Strong organizational and project management skills, with the ability to manage multiple priorities and timelines. - Excellent communication and stakeholder management skills, with the ability to translate complex information into clear, practical guidance. - A member-first, data-informed approach to identifying risks, measuring outcomes, and improving the experience. - Fluency with AI-enabled tools and the judgment to use them responsibly while maintaining high standards for accuracy and quality. - Demonstrated passion for performance, health and wellness, and the WHOOP mission. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The Ireland base salary range for this full-time position is €40,000 - 55,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.   In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Location: Boston, MA Workplace: OnSite At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Within Membership Services, we bring that mission to life by transforming every touchpoint into a catalyst for progress, so members feel equipped to rise to the moment, every moment. WHOOP is seeking a Change Management Team Lead to lead the team responsible for helping Membership Services successfully adopt, embed, and sustain operational change. This role will own and evolve the team’s change management framework, including change intake, impact assessment, sizing, governance, implementation planning, adoption measurement, and reinforcement. This is a people leadership role with accountability for developing Change Management Specialists, setting priorities, managing team capacity, and ensuring changes are delivered consistently and effectively. You will provide hands-on direction for complex or high-impact initiatives while empowering the team to independently manage changes across the Membership Services roadmap. You will partner closely with Membership Services leadership, Learning & Training, Quality, Knowledge Management, Support Operations, Launch Readiness, and other cross-functional teams to translate upcoming changes into coordinated, practical plans. Through strong leadership, structured planning, frontline engagement, data, and feedback, you will ensure changes land effectively with internal teams and enable Membership Services to consistently deliver the distinguished service our members expect. RESPONSIBILITIES - Lead, coach, and develop a team of Change Management Specialists, setting clear expectations, providing ongoing feedback, managing performance, and supporting career growth. - Operate and continuously improve the Membership Services change management framework, including intake, assessment, sizing, governance, planning standards, adoption measurement, and reinforcement. - Manage the team’s priorities and capacity, assigning work based on complexity, risk, business needs, and potential impact on the member experience. - Provide direction for change plans, ensuring they clearly define the intended member experience, employee impacts, communications, enablement needs, risks, ownership, and measures of success. - Lead or provide hands-on support for complex, high-risk, or highly visible changes, serving as an escalation point when barriers could affect adoption, operational performance, or the member experience. - Partner with Learning & Training, Quality, Knowledge Management, Support Operations, and Launch Readiness leaders to align deliverables, resolve dependencies, and prepare teams to support changes from launch. - Lead change governance discussions, providing senior stakeholders with clear visibility into upcoming changes, readiness, adoption risks, required decisions, and recommended actions. - Ensure member and frontline insights are incorporated into change decisions by using employee feedback, quality trends, process adherence, operational performance, and member contact data. - Oversee adoption and post-implementation monitoring, directing targeted communication, enablement, reinforcement, or remediation when gaps or unintended consequences emerge. - Ensure change plans account for impacts on AI-enabled support and automation, while promoting the thoughtful and responsible use of AI tools to improve how the team plans, analyzes, communicates, and delivers change. - Facilitate post-implementation reviews and use lessons learned to strengthen team practices, improve future change delivery, and reduce friction for members and employees. QUALIFICATIONS - 4+ years of experience in change management, program or project management, enablement, operations, or a related field, including direct people management experience. - Demonstrated ability to coach and develop team members, set priorities, manage performance, and build a collaborative, high-accountability team environment. - Experience leading change through planning, impact assessment, implementation, adoption, reinforcement, and post-launch evaluation. - Strong portfolio and organizational management skills, with the ability to balance multiple initiatives, resources, risks, and timelines. - Excellent communication and stakeholder management skills, with the ability to influence senior leaders, navigate competing priorities, and translate complexity into clear direction. - A member-first, data-informed approach to identifying risks, measuring outcomes, and improving both employee and member experiences. - Strong judgment and confidence operating in ambiguity, making decisions, escalating appropriately, and bringing structure to evolving initiatives. - Fluency with AI-enabled tools and the ability to guide their responsible use while maintaining high standards for accuracy, quality, and human judgment. - Demonstrated passion for performance, health and wellness, and the WHOOP mission. Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.   WHOOP is an Equal Opportunity Employer and participates in E-verify https://www.e-verify.gov/to determine employment eligibility   The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The U.S. base salary range for this full-time position is $60,000 - $80,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.   In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

• Development of machine learning and deep learning models. • Building solutions in NLP and Deep Learning.

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. 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.