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Location: San Francisco, CA | New York City, NY 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 Anthropic's Research Productivity organization builds the infrastructure and systems that accelerate research across Anthropic, including the tools that help our research process get faster and more effective over time. We're looking for an experienced software engineer to join us as we scale this infrastructure at a moment when both demand and scope are growing extremely quickly. This team operates like a startup within a startup. You'll be a strong fit if you like thinking from first principles, iterating fast on infrastructure, and tackling reliability and scalability challenges head-on as the products built on top of your systems evolve underneath you. You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make the architectural decisions that shape how the infrastructure behind our research tooling gets built. You'll partner directly with research teams to understand their workflows, anticipate how their requirements will change, and design and scale infrastructure that can keep pace. Responsibilities Design, build, and scale infrastructure and systems that support rapidly increasing usage, where requirements and workload continue to evolve as the products built on top of them evolve Independently scope and lead complex, multi-month engineering projects, from an ambiguous starting point through to a production system Drive cross-organizational alignment on technical direction, working through ambiguous problem spaces with multiple stakeholders and teams Make architectural decisions that shape the foundation of research infrastructure and tooling across Anthropic Partner directly with researchers to deeply understand their workflows, then anticipate and design for how those needs will change Iterate quickly, favoring pragmatic, first-principles solutions and fast feedback loops over heavy upfront design Take ownership of the reliability and scalability of critical systems as load, usage, and complexity increase Help set technical standards and best practices for the team, and mentor other engineers Minimum Qualifications Experience designing, building, and operating large-scale distributed systems or infrastructure in production A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects Strong software engineering fundamentals and hands-on coding ability Experience making architectural decisions that other engineers and teams build on top of Strong written and verbal communication skills, with experience driving alignment across multiple teams or stakeholders Demonstrated ability to operate effectively in ambiguous, fast-changing environments Strong candidates may also have Experience building infrastructure or platforms specifically for research or machine learning workflows Direct experience navigating the reliability and architectural challenges that come with rapidly scaling systems Experience with distributed systems, cloud infrastructure, and infrastructure-as-code Familiarity with the compute, tooling, and workflow needs of large-scale machine learning research Experience operating in a startup or startup-like environment, i.e. a small, fast-moving team with high autonomy Prior experience as a technical lead or mentor for other engineers 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: $405,000 — $625,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York; San Francisco ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We’re building a platform that covers the whole life of an LLM: training it, deploying it, and observing it in production. We already run multi-node training, elastic inference, sandboxes, and distributed volumes, and we control the infrastructure underneath. We’re looking for research depth in post-training to sit alongside our systems and product work. We are looking for research scientists with a strong track record in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. WHAT YOU’LL WORK ON: - Improve existing methods and develop new techniques for large-scale model training, optimization, and inference - Extend models to long-context and long-horizon tasks - Improve inference-time efficiency, reliability, and robustness in high-stakes real-world deployments YOU MAY BE A FIT IF: - You have a PhD in computer science, machine learning, or a related field - You have a demonstrated record of research accomplishments in reinforcement learning, machine learning, foundation models, or related fields - You have experience with large-scale training and inference infrastructure, including distributed systems and multi-node GPU clusters - You’ve developed, trained, optimized, or deployed state-of-the-art large-scale models - You have first-author publications at leading venues such as NeurIPS, ICML, ICLR, CoRL, CVPR, UAI, JMLR, or TMLR - You have a mission-driven mindset and a strong desire to translate research advances into meaningful product impact - You have a collaborative spirit and can work effectively across research and engineering teams Candidates with a master’s degree and significant research or industry experience will also be considered.

Location: New York; San Francisco ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: Most of the value of owning a model shows up at serving time. We’re building a platform that covers the whole life of an LLM (train it, deploy it, observe it), and inference is where teams feel the difference every day. We already run elastic inference, sandboxes, distributed volumes, and multi-node training, and we control the infrastructure underneath, so the serving stack is ours to shape rather than something we resell. You will do hands-on inference research at Modal, working with the research lead to pick high-impact bets and owning them end to end. The bets that matter most are the ones that move cost per token and tail latency on the workloads our customers actually run. WHAT YOU’LL WORK ON: - Own end-to-end inference research bets: speculative decoding, disaggregated prefill/decode, quantization (FP8, INT4), KV-cache and memory management, autoscaling for spiky serverless traffic, and whatever else the research agenda calls for - Train custom speculators against real production traffic and feed what you learn back into target models; acceptance length is the metric that decides the win - Work directly with customers alongside our Forward Deployed Engineers to deploy and tune models, and bring what you learn back into the research - Carry and expand collaborations with outside research labs, for example: - our work with ZLab on DFlash https://modal.com/blog/spec-is-all-u-need, a speculator design built on KV injection and blockwise parallel drafting - our work with SGLang on specdec https://modal.com/blog/host-overhead-inference-efficiency and multimodal inference https://modal.com/blog/boosting-multimodal-inference-performance-by-greater-than-10-with-a-single-python-dictionary performance - our work on Flash Attention 4 kernels https://modal.com/blog/flash-attention-4-faster - Work with engineering to turn frontier serving techniques into products: primitives for disaggregation, fast weight refresh for models that keep training after deployment, observability for quality and latency in production, or even a next-generation inference engine - Help shape the research agenda None of the above is prescriptive; your work will help guide our future. YOU MAY BE A FIT IF: - You have a research-leaning or systems background in LLM inference, with work you can point to - You’re fluent in the LLM serving stack, from kernels and quantization up to schedulers and autoscaling - You have a record of shipping research or systems that other people build on, whether in a lab or in industry - You have the drive to independently take a research bet from idea to result, working in the open with the rest of the team - You’re able to work in person in our NYC or San Francisco office

Location: Paris; London ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE Mistral AI is seeking Applied Scientist Interns and Research Engineer Interns to drive innovative research and collaborate with clients on complex research projects. You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas you will apply these models across a diverse set of use cases and domains. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions that turn the needle. WHAT YOU WILL DO - Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. - Generate and curate data for pre-training and post-training, working on evaluations and making sure the model's performance beats expectations. - Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment. - Collaborate with cross-functional teams to tackle complex use cases using agents and retrieval pipelines. - Manage research projects and communications with client research teams. WHAT WE'RE LOOKING FOR - Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences. - Expert with PyTorch or JAX. - Not afraid of contributing to a big codebase; finds their way around independently with little guidance. - Writes clean, readable, high-performance, fault-tolerant Python code. - Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence. - Low-ego, collaborative and eager to learn. - Track record of success through personal projects, professional projects or academia. NICE TO HAVE - Pursuing a PhD / Master in a relevant field (Mathematics, Physics, Machine Learning) — exceptional candidates from other backgrounds welcome. - Preferred duration: at least 6 months. Priority to candidates about to finalise their studies. - Research experience in agents, multimodal models, world models, robotics, diffusion models, cybersecurity, 3D understanding/generation, or time-series analysis. - Contributions to a large open-source or industry codebase. - Publications in top academic journals or conferences. - Enjoys improving existing code: typing, tests, CI pipelines. Location & work authorization: This internship is available only in France or the UK. Please apply only if you have the required work authorization to complete the internship in the relevant country for its full duration. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco, CA 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 an exceptional Research Engineer to join our Life Sciences team at Anthropic. Our team is organized around the north star goal of accelerating progress in the life sciences, from early discovery through translation, by an order of magnitude. Our team likes to think across the whole model stack. In this role, you'll combine your deep expertise in machine learning engineering to develop novel evaluation frameworks and training strategies that push the frontier of what AI can achieve in biology. You'll work at the intersection of cutting-edge AI and the biological sciences, developing rigorous methods to measure and improve model performance on complex scientific tasks. You'll collaborate closely with world-class researchers and engineers to build AI systems that can engage in all phases of research and development, while maintaining our commitment to safety and beneficial impact. Previous experience in life sciences is welcome, but not required for this role. Minimum Qualifications Demonstrated experience training and evaluating large language models Proficiency in Python and familiarity with modern ML development practices Experience building and managing data pipelines for large-scale datasets Comfortable navigating ambiguity and developing solutions in rapidly evolving research environments Strong written and verbal communication skills, with the ability to work independently while collaborating effectively across cross-functional teams Preferred Qualifications 8+ years of machine learning experience Prior work experience in AI and biology, including graduate studies (molecular biology, biochemistry, computational biology, or related fields) Experience working with large-scale biological datasets Published research or practical experience in scientific AI applications or long-horizon reasoning Background in reinforcement learning and/or pretraining Knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud deployment at scale Demonstrated ability to work across multiple domains, such as language modeling, systems engineering, and scientific computing Contributions to open-source scientific software or databases 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: $350,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale. This role focuses on the configuration and experimentation systems that let teams safely roll out changes, run controlled experiments, and make data-driven decisions across our products and infrastructure — from feature flagging and dynamic configuration to A/B testing platforms that support both research and production workloads. Responsibilities Own the technical strategy and roadmap for config and experimentation infrastructure, translating team-level goals into concrete execution plans and partnering with teams focused on deployment, testing, and more Maintain and enhance the architecture for feature flagging, dynamic configuration, and experimentation systems, ensuring the hardest problems get solved — whether by you directly or by working through others Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume experimentation and config workloads across all engineering teams Own and evolve the platforms and tooling that let engineers and researchers safely ship config changes, run experiments, and measure impact Define standards, tooling, and frameworks for experimentation and configuration management that drive developer productivity across research and production workloads You may be a good fit if you: Have deep experience with configuration management, feature flagging, and/or experimentation platforms in a large-scale environment Have strong proficiency in Python, Rust and/or Go Are obsessed with developer productivity and reducing friction in how teams configure, test, and ship changes Have experience with container orchestration and infrastructure at scale Have excellent communication skills and enjoy supporting internal partners to improve their development experience Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges Strong candidates may have: Have 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure Have 3+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams as an engineer or tech lead Experience with config or experimentation platforms such as Statsig, GrowthBook, LaunchDarkly, Optimizely, Unleash, or similar (including building such systems in-house) Experience designing experimentation frameworks — randomization, assignment, metrics pipelines, and statistical analysis for A/B testing at scale Experience with dynamic configuration systems and safe rollout mechanisms (gradual rollouts, kill switches, targeting rules) Experience building CLI tools, developer-facing services, and APIs/automation workflows that integrate config and experimentation into existing CI/CD pipelines Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Staff+ Software Engineer, Developer Acceleration About the Role Anthropic is seeking talented and experienced Staff+ Software Engineers to join Developer Acceleration within the Developer Productivity organization. The Developer Acceleration team is responsible for the infrastructure that enables thousands of employees to be productive via agents. By joining this team, you'll have a direct impact on the velocity and quality of Anthropic's research and engineering development. You will be defining how AI transforms our work and building the future of agentic productivity. Some things that the team owns: Agent Runtime Platform for provisioning and running agents Knowledge for providing relevant internal context to agents and humans Some of our work is mentioned in When AI Builds itself and Building effective human-agent teams . Responsibilities Define the future of agentic productivity at scale and at the frontier Own the technical strategy and roadmap for your area, translating goals into concrete execution Define what quality means for agent-driven engineering work, and hold that line across the company Stay hands-on: build and ship the runtime platform and tooling Build agent harnesses and experiment with various context management strategies to improve agent performance and correctness Write evals to benchmark agent behaviors Deliver impact by collaborating cross-team Own infrastructure scalability and reliability, and establish operational excellence practices You May Be a Good Fit If You: Have 10+ years building and operating large-scale distributed systems Have 3+ years of experience leading large scale, complex projects or teams as an engineer or tech lead Have a lot of experience with agents, eg. agents doing technical/knowledge work Are obsessed with productivity and transforming how we work Have experience building scalable platforms Have excellent communication skills and enjoy supporting internal partners Strong Candidates May Also Have: Deep understanding of, and care for, how human work will evolve; and a drive to help shepherd that transition Experience with container or VM orchestration at scale Experience working with researchers and engineers Developer productivity or infrastructure experience, such as CI/CD, builds, etc. Experience building widely adopted CLI tools and services Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY 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 Anthropic's Enterprise Knowledge Work team builds the products that help enterprise knowledge workers collaborate deeply with Claude for major parts of their work. Over the past year, AI has transformed how software engineering happens; for the rest of knowledge work, though, using AI still mostly means answering questions and producing first drafts — a small slice of the actual job. We're building toward something bigger: people and agents working together on every core work objective, from first idea to finished product, and the recurring work of a team running with Claude in the loop instead of a person pushing every step. It's an enormous space, it's early, and no one has built it well yet. You'll help decide what these products are, not just how they're built — the product questions are as open as the architecture ones — and you'll see your work land with real teams at the world's largest enterprises. What you'll do Own technical design and delivery for enterprise-facing core products, end-to-end across the stack Partner with product, design, and go-to-market to turn enterprise customer workflows into shipped product, not just execute against a spec Set technical direction and standards for your team: architecture, code quality, and how the team builds Work directly with enterprise customers and sales during key conversations, translating what you learn into engineering priorities Work closely with research to make the models better in your domain: shaping evals, surfacing failure modes, and feeding customer learnings back into model development Mentor other engineers and raise the technical bar across the team, working with influence rather than authority Build the core primitives that enable knowledge workers across industries and roles to meaningfully leverage Claude You may be a good fit if you Have 8+ years of software engineering experience, ideally with 2+ years at a Staff or equivalent technical leadership level Have led the design and delivery of complex customer-facing products across the full stack Have built AI products and know what it takes to turn model capabilities into applications people actually use Are comfortable working directly with enterprise customers and translating what you learn into technical decisions Have built products from 0 to 1 in fast-moving environments, and can set technical direction with limited precedent to lean on Drive cross-team alignment to ship impactful work, with influence over authority Strong candidates may also have Experience working with research to improve domain-specific model capabilities, including evaluation frameworks Experience as startup founders or early-stage employees 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: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY 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 Enterprise is central to Anthropic's mission. The organizations that could benefit most from Claude often have the most demanding needs, with rigorous requirements around end-user experience, procurement, security, and permissions. We believe earning their trust is essential to ensuring AI benefits the world broadly. We're looking for a Staff+ Platform Engineer for our Enterprise pillar—the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, the systems you design—identity, permissions, governance, connectivity, and the data foundations beneath them—are what make it possible. This is a high-agency role: you'll design the abstractions other teams want to adopt, help the team evaluate hard tradeoffs, and be the engineer in the room who can interface with executives and security teams from the world's largest companies. What you'll do Define and drive multi-year technical strategy for foundational enterprise systems, including our distributability and multi-cloud direction Identify and personally lead the highest-complexity, highest-impact engineering initiatives spanning multiple teams Serve as a primary technical decision-maker for major architectural decisions with org-wide scope Design the platform primitives—identity, permissions, governance, connectivity, and usage data—that other product teams build on Partner with teams such as Inference and Platform on foundational systems, Customer Success for the voice of the customer, and Infrastructure and Safeguards on security, privacy, and responsible deployment Mentor and develop senior engineers across the org, and drive alignment across Product, GTM, and Customer Success while proactively addressing systemic technical risks You may be a good fit if you Have 8+ years of engineering experience with a clear track record operating at Staff or equivalent technical leadership level Have deep expertise in distributed systems and API architecture, and are effective writing design docs, making architectural calls, and coding in critical paths Have shaped technical strategy at a Cloud Service Provider or large-scale Enterprise SaaS company Bring strong domain expertise and intuition in enterprise areas such as security, identity, compliance, governance, permissions, and connectivity Drive the highest-leverage technical outcomes without formal authority—you lead through influence, quality of thinking, and trust Are highly effective across org boundaries—you build trust with GTM, Platform, Inference, Infrastructure, Privacy, Safeguards, and business stakeholders alike Strong candidates may also have Experience with multi-cloud or distributable deployments of complex systems Experience building the data foundations for enterprise administration—entitlements, metering, usage and cost visibility 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: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: 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 The Computer Use team focuses on teaching Claude to see, use, and understand computer interfaces. As a Research Engineer on the team, you'll work on advancing our models' ability to reliably and safely operate real software. We're looking for someone who's genuinely excited about both the research and the product sides of computer use. Your work will translate directly into model improvements in our own and our customers' products. You can try Claude's computer use capabilities today through the Claude in Chrome extension and Claude Cowork. Key Responsibilities: Design and run experiments to improve Claude's perception and agentic capabilities Develop robust, reliable evaluation frameworks for measuring our models' ability to complete complex computer tasks Build and improve computer use and vision reinforcement learning training environments Create pipelines and tools to test and validate complex RL environments Collaborate with teams across the model training and infrastructure stack to improve our production training setup Partner with product teams to bring research advances into production Minimum Qualifications: Software engineering experience and proficiency in Python Experience training, fine-tuning, or evaluating machine learning models Strong communication skills and a collaborative working style Care about the societal impacts and safety of your work Preferred Qualifications: Experience training models for computer use or other agentic capabilities Experience with reinforcement learning, particularly in long-horizon or sparse-reward settings Familiarity with multimodal model training Experience building evaluations or benchmarks for agentic systems Experience building reinforcement learning environments, simulation systems, or large-scale ML infrastructure Experience working closely with product teams to drive model improvements The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Paris; London Workplace: Hybrid TL;DR: We're looking for a research engineer to build and maintain our internal suite of benchmarks, covering single/multi-turn content and agentic guardrails. The research engineer would also work with the team on projects studying agent behaviours in the wild. About us White Circle http://whitecircle.com is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale. - We’ve recently raised our Series A funding round, taking our total funding to $70M. Our investors include top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others - We process over 100M+ API calls every month - We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need. About the team White Circle's fundamental research team works on the science of how AI systems fail in the real world: where agents break, how misalignment actually looks like to the end user, and how it is present in the model internals. We build the evals, benchmarks, environments, and tooling that empirically study high-impact agent reliability concerns — some of which become the guardrails shipped in our products, and some of which become public writeups. What you’ll do Own and maintain our internal benchmark suite, covering single/multi-turn content guardrails and agentic safety. - Build benchmarks that distinguish specific model capabilities. - Work with the product team to build evals covering core functionality of our flagship models. - Build benchmarks for new features coming out of the research team. - Adapt and extend evals to new verticals and changing product data. - Work on research projects that study and quantify realistic agentic and LLM failure modes in the wild. You’ll fit right in if you - Have built an LLM benchmark from scratch that distinguished specific model capabilities (i.e., produced a measurable, defensible capability difference, not just a score). - Have built synthetic data for post-training textual or multimodal models. - Can reproduce a published benchmark result and identify where the original methodology is fragile or misleading. - You write Python that other people can build on. Our whole stack is Python; we want someone who has shipped and maintained production code and who factors messy problems into clean abstractions others can extend. - You can write efficient LLM inference setups, including sensible orchestration of parallel calls, retries, rate-limit handling. - An AI power-user — fluent with frontier models and coding agents day to day. A big plus - Automated red-teaming experience - Have worked across a range of agentic scaffolds and reproduced public benchmark results on them - Strong knowledge of existing reward-model / monitoring / safety benchmarks - One or more published papers in the evals / safety-evaluation space Compensation & benefits - Competitive compensation, including equity - Flexible time off - Office in central London/Paris with flexible hybrid setup - Relocation support if you’re moving to Paris, available after your probationary period - Premium private health insurance - Mental health support, including coverage for therapy when you need it - Lunch and dinner covered when you work from the office - Learning and development support for courses, conferences, and opportunities to grow your skills - All the hardware, subscriptions, tools, and services you need - Team off-sites twice a year: we’ve recently been to the Alps, Saint-Tropez, and Marbella Process 1. Intro call with Talent 2. Test assignment 3. Technical interview with Head of Fundamental Research 4. Final interview with CEO

Location: Hong Kong Nex is on a mission to help families rediscover the joy of movement. Created by parents for parents, Nex combines technology and play to deliver fun, social, and interactive experiences powered by natural body motion, encouraging kids and adults to move more, play more, and have fun together. Nex Playground, the company’s award-winning active play system, is purpose-built to get families moving year-round, with safety and privacy as core considerations in its intentional design. It is certified kidSAFE+ COPPA compliant and built to support healthy, active play for all ages and abilities. Nex Playground features a growing library of 50+ experiences, including motion and dance games, fitness and educational experiences, and Nex Originals. Content includes collaborations with partners like Hasbro, Sesame Workshop, and NBCUniversal. Nex has been recognized by Fast Company’s Most Innovative Companies, TIME’s Best Inventions, and Parents’ Best Entertainment System for Families, and has earned Red Dot, IDEA, and Core77 international design awards. We encourage you to explore Have Fun and Is Motion Gaming Back? , as they offer a deeper look into our culture, values, and explain how our approach to motion gaming differs from previous generations. Nex employees may be expected to collaborate with colleagues across different time zones. Depending on the role and location, occasional travel may also be required for company events, external meetings, and other business-related activities. Important Notice: ⚠️ To protect yourself from recruitment scams, please note that Nex communicates through official company emails ending in @nex.inc . If you receive a suspicious email or message, please do not respond and report it immediately to us. Location: Hong Kong Type: Full Time The Role As a Software Engineer at Nex, you will contribute to building the technical foundations that power our platform's most demanding capabilities. In the Framework Engineering track, you will own the design and development of our cross-platform software framework for detection, sensing, haptics, and ML inference. You will build the real-time systems, hardware abstraction layers, and developer APIs that enable multimodal interaction on Nex Playground. The offers the opportunity to work on deeply technical problems in machine learning systems, data infrastructure, sensing technologies, and real-time inference. You will be part of a small, highly technical team that values both specialization and collaboration, with clear ownership of core technology areas. The Mindset You are drawn to solving complex technical challenges at the intersection of research and production engineering. You care deeply about building systems that are reliable, performant, and maintainable. You thrive in environments where technical depth matters, where your expertise in ML systems, distributed computing, or real-time software directly shapes what the platform can do. What You’ll Do Design and develop a robust, performant, cross-platform framework for sensing, detection, haptics, and ML inference Build efficient runtime execution systems and hardware abstraction layers Develop developer APIs that make complex sensing and inference accessible Optimize for real-time performance on multimodal data streams Work on camera, microphone, and haptics integration Implement code that runs reliably across different platforms and hardware configurations Improve framework stability, performance, and developer experience Write clean, well-tested code that maintains high engineering standards Participate in code reviews and help raise the engineering bar across the team Contribute to shared tools, infrastructure, and cross-role projects (20% Time) Work with the dual-leadership model (Engineering Manager and Tech Lead) to understand priorities and technical direction Document systems and decisions to support team knowledge sharing Must Have 3+ years of professional software engineering experience in building real-time software frameworks, cross-platform systems, or performance-critical applications Proficiency in C++/C#, additional experience with at least one other systems language (C++, C#, Java, Rust, or Go) Experience with cross-platform development Proven track record with performance optimization, real-time systems, or hardware abstraction layers Experience building developer APIs or software frameworks used by other engineers Nice To Have Experience building real-time systems or low-latency software Familiarity with computer vision, signal processing, or embedded systems Experience with cross-platform development or hardware abstraction Knowledge of performance optimization and profiling Experience with sensing technologies (cameras, microphones, or similar) Familiarity with CI/CD pipelines and automated testing Experience working in small, high-performance technical teams Background in startups, high-growth environments, or consumer product companies Passion for pushing technical boundaries and deep problem-solving We Offer Competitive compensation package. Flexible working hours and vacation policy. Product-driven culture that treasures talents and individual growth. Front-row seat and hands-on experience with cutting edge technologies in the evolving gaming field Nex is located in San Jose, California, USA and Hong Kong . Learn more about us at https://www.nexplayground.com/about . We encourage applications even if you don’t meet more than 50% of the requirements — we believe that experience comes in many forms! Nex is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex (including pregnancy, childbirth, gender identity, and sexual orientation), national origin, ancestry, age, physical or mental disability, medical condition, genetic information, marital status, military or veteran status, or any other characteristic protected by applicable law. This policy applies to all individuals at every stage of the employment relationship, including all current and prospective employees, and covers all employment decisions including recruitment, hiring, job assignment, promotion, compensation, benefits, training, discipline and termination. We are committed to providing a workplace free from discrimination and harassment and to fostering an inclusive environment for all employees.

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 looking for a Commercial Counsel, SPARC (Safety, Policy, and Research Contracts) to join our legal team at the forefront of shaping how cutting-edge AI technology reaches users, researchers, and enterprises worldwide. You'll work alongside experienced colleagues who operate as true strategic partners—moving fast, thinking creatively, and working collaboratively on cutting-edge AI safety and research agreements, including threat-sharing frameworks with leading security organizations and collaborations that shape and advance responsible AI development standards. This is an excellent opportunity for a motivated attorney to develop deep expertise in their commercial transactions career while contributing directly to responsible AI development. Key responsibilities Draft, review, and negotiate commercial agreements, focusing mainly on AI safety and research agreements, as well as product and strategic partnership agreements Partner closely with beneficial deployments, health, policy, and education partnerships teams to support deal velocity and provide practical legal guidance Draft program terms for the phased deployment of AI models with frontier capabilities in cybersecurity and health sciences. Help build and maintain commercial legal infrastructure, including contract templates, playbooks, and process improvements Partner with Policy, Safeguards, and Research teams on novel AI governance initiatives Identify and escalate legal risks appropriately while supporting business momentum Stay current on legal developments affecting AI technologies Minimum qualifications Hold a law degree (JD, LLB, or equivalent) and meet the local licensing requirements to work as in house counsel where you’ll be based Experience drafting, reviewing, and negotiating commercial agreements Demonstrated ability to provide clear, practical legal guidance to non-lawyers on complex commercial law matters Preferred qualifications Commercial experience supporting research collaborations and sponsored research and grant giving programs Curiosity about AI technology and AI policy, and a commitment to responsible AI development Experience with biotech, clinical research, or other life sciences transactions Familiarity with grant-making or grant-funded arrangements, including funding terms and compliance considerations Experience advising on partnerships with non-profit foundations, academic institutions, or industry trade groups Comfort advising research teams whose work doesn't follow a standard commercial playbook Strong communication skills, with the ability to translate legal concepts for non-legal audiences A collaborative approach to working with colleagues and external partners Experience navigating multi-stakeholder agreements involving technical and policy considerations Ability to adapt to shifting priorities in a fast-paced environment Experience with SaaS agreements or other technology transactions 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: $265,000 — $335,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Warsaw ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE ROLE As an AI Scientist, you will push the boundaries of AI by developing and scaling cutting-edge models. This role exists to advance Mistral’s mission of democratizing frontier intelligence, enabling businesses and consumers to benefit from open, high-impact AI systems. You will collaborate with a global, cross-functional team to design, build, and deploy models that solve real-world problems across reasoning, code, and multimodal applications. Your work will directly shape how AI integrates into daily life and enterprise operations. What will you do   • Research and develop novel methods to push the frontier of large language models • Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech) • Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale • Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact   What we're Looking for   • You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java) • You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes) • You have high engineering competence. This means being able to design complex software and make it usable in production • You are a self-starter, autonomous and a team player   Now, it would be ideal if   • You have hands-on experience with training large transformer models in a distributed fashion • You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment • You have a strong publication record in a relevant scientific domain   Note that this is not an exhaustive or necessary list of requirements. Please consider applying if you believe you have the skills to contribute to Mistral's mission. We value profile and experience diversity. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

Location: San Francisco, CA | 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 Anthropic is seeking an exceptional Legal Program Manager to serve as the operational backbone of contracting for the Compute and Infrastructure team. We'll rely on you to manage a high volume of procurement and vendor agreements — including datacenter colocation, lease, and build-to-suit agreements; hardware, chip, and network-equipment procurement; and construction, facilities, and operations-and-maintenance (O&M) contracts — along with the NDAs, order forms, SOWs, and amendments that surround them. You will build the scalable contracting processes — templates, playbooks, intake and approval workflows, and contract lifecycle management — that let the business move at the speed of Anthropic’s infrastructure buildout. This role owns the system, throughput, and visibility that move every agreement from intake through signature. Key responsibilities Coordinate and shepherd a high volume of compute and infrastructure procurement transactions — datacenter colocation, lease, and build-to-suit agreements; hardware, chip, and network-equipment procurement; construction/EPC and facilities/O&M agreements; and the supporting NDAs, order forms, SOWs, and amendments — driving each from intake through signature Own and administer the contract lifecycle management system: workflow design and configuration, templates, approval routing, signing and archive and integrity hygiene Design and run intake and triage: how requests enter, how they are prioritized, and how they route to the right owner Propose and develop scalable solutions to improve contracting efficiency and throughput across the infrastructure vendor base Collaborate with business units and legal team members to streamline contract management processes, manage post-signature obligations and renewals across the infrastructure vendor portfolio, identify potential risks, and drive continuous improvement in contract handling efficiency Partner closely with the Compute and Infrastructure, Product, Finance, Security, Business Operations, and Procurement Ops teams to achieve key business objectives and deliver strategic, business-minded, and solutions-focused counsel Build reporting, dashboards, SLAs, and the metrics that surface turnaround times and bottlenecks across the infrastructure vendor portfolio Deploy LLM and AI tooling to scale contracting throughput and reduce manual handling Minimum Qualifications Experience operating in a fast-paced technology startup in which priorities shift rapidly and schedules "move to the left," thriving in this dynamic environment and priding yourself on your adaptability and ability to pivot with speed and grace Initiative and autonomy in managing complex contractual matters, effectively prioritizing competing deadlines An understanding of what's important in the context of a contract, the organization's mission, and enough contract fluency to triage and route requests, track obligations, and pull in relevant legal counsel Excitement to grow with an organization and help shape the culture of the commercial function A preference for straightforward, concise explanations over legalese and overwrought drafting A knack for identifying and implementing efficient processes and policies The ability to thrive as a member of cross-functional teams building frontier technologies, with a desire to develop a deep understanding of the Compute & Infrastructure teams and the datacenter, hardware, and network systems they build and operate Comfort operating outside your areas of expertise and in uncharted legal territory A "doer" mentality, willing to roll up your sleeves to get things done as a team player who doesn't hesitate to jump in to do work that needs to get done, whether glamorous or not Hands-on experience with contract lifecycle management or legal-operations tooling, process design, and working from data, metrics, and dashboards Comfort using AI and LLM tools to streamline and scale routine contracting work Preferred Qualifications 10+ years in contract management, legal operations, or procurement operations, including hands-on experience implementing or administering a contract lifecycle management (CLM) platform; experience supporting infrastructure, datacenter, hardware, construction, or telecom/network procurement and vendor contracting Proven ability to collaborate across various organizational levels and functions to facilitate efficient contracting processes and execution while building strong relationships Working familiarity with the structure of datacenter, colocation, and lease agreements; hardware and equipment procurement; construction, facilities, and O&M contracts; network and telecom agreements; high-volume, template-driven vendor contracting; and general contract terms Excellent verbal and written communication, analytical, collaboration, and interpersonal skills Motivated self-starter able to multitask and juggle multiple priorities in a dynamic environment Authentic integrity and a deep understanding of the importance of ethics in business Experience implementing or administering a CLM platform (Ironclad) and standing up reporting and metrics 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: $285,000 — $340,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: London, UK 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 Anthropic is seeking a Contracts Manager to join our team in London. Embedded within our in-region commercial and legal operations, you'll work closely with local in-region counsel and lead counsel to support commercial and technology transactions across the region. We'll rely on you to help review, draft, and negotiate commercial and procurement contracts that support our cutting-edge AI systems. You'll also serve as a key partner in translating global legal strategy into regional execution — including supporting the triage of regional matters, rolling out process improvements and initiatives driven from global headquarters, and running local enablement sessions to keep business teams informed and aligned. You'll build scalable contracting processes and collaborate across Product, Sales, Finance, Business Operations, Research, and Procurement teams. Key responsibilities Draft, analyze, negotiate, and complete complex commercial transactions with our enterprise customers, vendors, and strategic partners, including IP licensing agreements Propose and develop scalable solutions to improve contracting efficiency Collaborate with business units and legal team members to streamline contract management processes, identify potential risks, and drive continuous improvement in contract handling efficiency Collaborate with the Product, Sales, Business Operations, Research, and Procurement teams to achieve key business objectives and deliver strategic, business-minded, and solutions-focused counsel Partner closely with in-region counsel and lead counsel on day-to-day triage of regional legal matters, ensuring workload is prioritized effectively and seamlessly coordinated between regional and global teams Drive the regional rollout of process improvements, policy updates, and programs initiated from global headquarters, including planning and facilitating local enablement sessions to keep commercial and cross-functional stakeholders informed and ready to execute Pitch in across other areas of the legal function — as a small team supporting big things, each of us practices across multiple areas, and we'd love to hear where else your experience or interests could contribute Minimum qualifications Substantive knowledge of software and SaaS agreements, reseller agreements, services agreements, strategic partnerships, and general commercial contract terms Ability to independently draft, review, and negotiate complex commercial and procurement contracts Experience managing the full contract lifecycle for technology transactions, sales organizations, and/or partnerships Preferred qualifications 8+ years of related contract management experience, with at least 5 years supporting technology transactions, sales organizations, and/or partnerships Experience operating in a fast-paced technology startup where priorities shift rapidly and schedules "move to the left" Prior experience as part of a global or distributed legal team, including partnering with colleagues across regions and navigating the nuances of aligning local needs with centralized priorities A track record of operating with a high degree of autonomy while keeping global stakeholders appropriately informed — comfortable setting your own cadence and exercising sound judgment about when to escalate versus when to decide Strong habits around async communication, proactive status updates, and operating effectively with a remote manager across time zones An understanding of what's important in the context of a contract and the organization's mission, including when to be flexible and when to draw a hard line A knack for identifying and implementing efficient processes and policies A preference for straightforward, concise explanations over legalese and overwrought drafting Comfort operating outside your areas of expertise and in uncharted legal territory The ability to thrive as a member of cross-functional teams building frontier technologies, with a desire to develop a deep understanding of our technical teams and what we are building Excellent verbal and written communication, analytical, collaboration, and interpersonal skills Authentic integrity and a deep understanding of the importance of ethics in business 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: £140,000 — £180,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco; Sunnyvale Workplace: Hybrid About Cantina: Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning. If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future! About the Role: We are building a core team to develop next-generation native video and omni foundation models for multimodal generation and understanding. Our current focus is large-scale video foundation model development, spanning pre-training, continued training, and post-training for high-quality, controllable, consistent, and efficient generation. Our broader roadmap includes reference- and memory-based generation, multimodal understanding and interaction, and joint audio-video generation. In this role, you will work on foundational research and large-scale model development across the full model lifecycle, including architecture, data, training, evaluation, post-training, training systems, and efficient inference. You will have the opportunity to shape both the technical direction and the team from an early stage. What You’ll Do: - Research, develop, and scale native video and multimodal foundation models, from early prototypes through large-scale pre-training, continued training, and post-training. - Explore new model architectures, training objectives, and conditioning mechanisms for video generation, reference- and memory-based generation, multimodal interaction, and joint audio-video generation. - Build and improve large-scale data curation, distributed training, evaluation, and post-training pipelines for high-quality and controllable generation. - Design systematic experiments to understand model scaling, generation quality, controllability, consistency, robustness, and inference efficiency. - Collaborate closely with researchers, engineers, and product teams to help shape the technical roadmap and, where appropriate, translate model advances into real-world capabilities. - Contribute to research publications and open-source releases when appropriate. What You’ll Bring: - Strong research and engineering experience in generative modeling, including areas such as diffusion models, flow matching, DiTs, video generation, multimodal models, world models, or related fields. - Hands-on experience training and evaluating large-scale image, video, or unified multimodal models using modern deep learning frameworks and distributed training systems. - A strong track record of developing impactful models or systems, demonstrated through research publications, open-source contributions, production impact, or other significant technical work. - Ability to independently own ambiguous research problems, move effectively from ideas to experiments, and work well in a highly collaborative environment. - Specialized depth in one or more areas across the foundation model lifecycle, such as model architecture, data curation, controllable generation, multimodal understanding and conditioning, post-training and reward modeling, model acceleration, inference systems, or deployment. Compensation: The anticipated annual base salary range for this role is between $200,000-$320,000. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data. Benefits: - Competitive salary and generous company equity - Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina - 42 days of paid time off, including: - 15 PTO days - 10 sick days - 15 company holidays - 2 floating holidays - Generous parental leave & fertility support - 401(k) retirement savings plan - Lifestyle spending account – $500/month to use however you’d like - Complimentary lunch and snacks for in-office employees - One Medical membership, and more!

Location: United States Workplace: Remote At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀 ROLE OVERVIEW You'll own and evolve the AI systems behind ClickUp's voice platform: real-time streaming transcription, intelligent reformatting, context-aware mention detection, and voice-to-action pipelines. This is a high-impact, hands-on role where you'll push the boundaries of what voice interfaces can do inside a productivity tool used by millions.   KEY RESPONSIBILITIES - Design, build, and optimize real-time speech-to-text pipelines (streaming ASR, VAD, audio processing) - Improve transcription accuracy through context injection (user names, teams, custom vocabulary, language detection) - Develop and maintain LLM-powered post-processing (grammar correction, filler removal, mention resolution, formatting) - Build voice-to-action systems that parse natural language into structured workspace commands - Evaluate, benchmark, and integrate ASR models (Whisper, AssemblyAI, Fireworks, etc.) for cost, latency, and accuracy - Collaborate with product and platform teams to ship voice features across MAX Desktop, Mobile, Web, and Browser Extension - Explore multimodal AI capabilities (screen + voice + text) for next-gen assistant experiences Equal Opportunity Employer ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. Privacy Notice ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice. https://clickup.com/careers-terms/candidate-privacy-notice If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice https://t333.s.clickup-attachments-stg.com/t333/d9a53ce2-6d2c-48cd-84b1-ed4e525f9613/Philippine%20Data%20Privacy%20Notice_2024.pdf?view=open for further details. Visa Sponsorship Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions. Fraud Alert ClickUp Talent Acquisition will only initiate contact via an @clickup.com http://clickup.com email or through our official careers portal on clickup.com http://clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com. AI Processing Notice ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates' employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.