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However, some roles may require more time in our offices</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;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</li>\n</ul>\n<p><strong>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&#39;re interested in this work.</strong></p>\n<p><strong>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&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>\n<p><strong>How we&#39;re different</strong></p>\n<p>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. 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You will have passion for making powerful technology safe and beneficial.</p>\n<p>The annual compensation range for this role is £225,000 - £240,000GBP.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_4b5aec44-56d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5116274008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"£225,000 - £240,000GBP","x-skills-required":["AI engineering","Python","LLM-powered applications","agent architectures","evaluation frameworks","deployment at scale"],"x-skills-preferred":["pair programming","architecture reviews","code contributions","custom evaluation frameworks","scalable architectures","technical documentation","evaluation suites","AI engineering techniques","architecture diagrams"],"datePosted":"2026-03-08T13:56:14.802Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"AI engineering, Python, LLM-powered applications, agent architectures, evaluation frameworks, deployment at scale, pair programming, architecture reviews, code contributions, custom evaluation frameworks, scalable architectures, technical documentation, evaluation suites, AI engineering techniques, architecture diagrams","baseSalary":{"@type":"MonetaryAmount","currency":"GBP","value":{"@type":"QuantitativeValue","minValue":225000,"maxValue":240000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_20d39f2a-da8"},"title":"TPU Kernel Engineer","description":"<p><strong>About the Role</strong></p>\n<p>As a TPU Kernel Engineer, you&#39;ll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimising kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance.</p>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have significant experience optimising ML systems for TPUs, GPUs, or other accelerators</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n<li>Want to learn more about machine learning research</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>High performance, large-scale ML systems</li>\n<li>Designing and implementing kernels for TPUs or other ML accelerators</li>\n<li>Understanding accelerators at a deep level, e.g. a background in computer architecture</li>\n<li>ML framework internals</li>\n<li>Language modeling with transformers</li>\n</ul>\n<p><strong>Representative projects:</strong></p>\n<ul>\n<li>Implement low-latency, high-throughput sampling for large language models</li>\n<li>Adapt existing models for low-precision inference</li>\n<li>Build quantitative models of system performance</li>\n<li>Design and implement custom collective communication algorithms</li>\n<li>Debug kernel performance at the assembly level</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>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.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;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.</li>\n</ul>\n<p><strong>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&#39;re interested in this work.</strong></p>\n<p><strong>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&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>\n<p><strong>How we&#39;re different</strong></p>\n<p>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&#39;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.</p>\n<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p><strong>Come work with us!</strong></p>\n<p>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.</p>\n<p><strong>Guidance on Candidates&#39; AI Usage:</strong></p>\n<p>Learn about our policy for using AI in our application process</p>\n<p><strong>Apply for this job</strong></p>\n<ul>\n<li>indicates a required field</li>\n</ul>\n<p>First Name<em> Last Name</em> Email<em> Country</em> Phone* 244 results found No results found</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_20d39f2a-da8","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4720576008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$280,000 - $850,000USD","x-skills-required":["TPU","GPU","ML systems","kernel design","optimisation","pair programming","machine learning research","societal impacts"],"x-skills-preferred":["high performance","large-scale ML systems","computer architecture","ML framework internals","language modeling with transformers"],"datePosted":"2026-03-08T13:51:07.394Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"TPU, GPU, ML systems, kernel design, optimisation, pair programming, machine learning research, societal impacts, high performance, large-scale ML systems, computer architecture, ML framework internals, language modeling with transformers","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":280000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_447c26bd-a83"},"title":"Research Engineer, Universes","description":"<p><strong>About the Role</strong></p>\n<p>We&#39;re looking for Research Engineers to help us build the next generation of training environments for capable and safe agentic AI. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Build the next generation of agentic environments</li>\n<li>Build rigorous evaluations that measure real capability</li>\n<li>Collaborate across research and infrastructure teams to ship environments into production training</li>\n<li>Debug and iterate rapidly across research and production ML stacks</li>\n<li>Contribute to research culture through technical discussions and collaborative problem-solving</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Are highly impact-driven — you care about outcomes, not activity</li>\n<li>Operate with high agency</li>\n<li>Have good research taste or senior technical experience, demonstrating good judgment in identifying what actually matters in complex problem spaces</li>\n<li>Can balance research exploration with engineering implementation</li>\n<li>Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems</li>\n<li>Are comfortable with uncertainty and adapt quickly as the landscape shifts</li>\n<li>Have strong software engineering skills and can build robust infrastructure</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n</ul>\n<p><strong>Strong candidates may also have one or more of the following:</strong></p>\n<ul>\n<li>Have industry experience with large language model training, fine-tuning or evaluation</li>\n<li>Have industry experience building RL environments, simulation systems, or large-scale ML infrastructure</li>\n<li>Senior experience in a relevant technical field even if transitioning domains</li>\n<li>Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems</li>\n<li>Published influential work in relevant ML areas</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<ul>\n<li>Education requirements: We require at least a Bachelor&#39;s degree in a related field or equivalent experience.</li>\n<li>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.</li>\n<li>Visa sponsorship: We do sponsor visas! However, we aren&#39;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.</li>\n</ul>\n<p><strong>How we&#39;re different</strong></p>\n<p>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&#39;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.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_447c26bd-a83","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5061517008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$500,000 - $850,000 USD","x-skills-required":["reinforcement learning","training environments","evaluation methodologies","software engineering","pair programming"],"x-skills-preferred":["large language model training","RL environments","simulation systems","distributed systems","influential work in ML areas"],"datePosted":"2026-03-08T13:49:07.277Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, Seattle, WA, New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"reinforcement learning, training environments, evaluation methodologies, software engineering, pair programming, large language model training, RL environments, simulation systems, distributed systems, influential work in ML areas","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":500000,"maxValue":850000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9d8e34bd-10a"},"title":"Research Engineer / Research Scientist, Tokens","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;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.</p>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have significant software engineering experience</li>\n<li>Are results-oriented, with a bias towards flexibility and impact</li>\n<li>Pick up slack, even if it goes outside your job description</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n<li>Want to learn more about machine learning research</li>\n<li>Care about the societal impacts of your work</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>High performance, large-scale ML systems</li>\n<li>GPUs, Kubernetes, Pytorch, or OS internals</li>\n<li>Language modeling with transformers</li>\n<li>Reinforcement learning</li>\n<li>Large-scale ETL</li>\n</ul>\n<p><strong>Representative projects:</strong></p>\n<ul>\n<li>Optimizing the throughput of a new attention mechanism</li>\n<li>Comparing the compute efficiency of two Transformer variants</li>\n<li>Making a Wikipedia dataset in a format models can easily consume</li>\n<li>Scaling a distributed training job to thousands of GPUs</li>\n<li>Writing a design doc for fault tolerance strategies</li>\n<li>Creating an interactive visualization of attention between tokens in a language model</li>\n</ul>\n<p><strong>Annual compensation range for this role is listed below.</strong></p>\n<p>Annual Salary:</p>\n<p>$350,000 - $500,000USD</p>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> 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.</p>\n<p><strong>Visa sponsorship:</strong> We do sponsor visas! However, we aren&#39;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.</p>\n<p><strong>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&#39;re ever unsure about a communication, don&#39;t click any links—visit anthropic.com/careers directly for confirmed position openings.</strong></p>\n<p><strong>How we&#39;re different</strong></p>\n<p>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&#39;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.</p>\n<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>\n<p><strong>Come work with us!</strong></p>\n<p>Anthropic is a public benefit corporation headquartered in California, USA.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9d8e34bd-10a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://job-boards.greenhouse.io","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4951814008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$350,000 - $500,000USD","x-skills-required":["software engineering","machine learning research","high performance","large-scale ML systems","GPUs","Kubernetes","Pytorch","OS internals","language modeling","reinforcement learning","large-scale ETL"],"x-skills-preferred":["pair programming","collaboration","communication skills"],"datePosted":"2026-03-08T13:46:19.922Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City, NY; Seattle, WA; San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"software engineering, machine learning research, high performance, large-scale ML systems, GPUs, Kubernetes, Pytorch, OS internals, language modeling, reinforcement learning, large-scale ETL, pair programming, collaboration, communication skills","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":350000,"maxValue":500000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_7d5a8f0f-540"},"title":"Research Engineer, Agents","description":"<p><strong>About Anthropic</strong></p>\n<p>Anthropic&#39;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.</p>\n<p><strong>About the role:</strong></p>\n<p>Agentic systems are becoming an increasingly important part of how AI is deployed. Over the last year, we’ve seen rapid adoption of Claude-powered agentic systems in spaces like coding, research, customer support, network security, and more. We believe this is just the beginning, and we expect Claude to be handling much more complex tasks end-to-end or in cooperation with a human user as time goes on. We have a team striving to make Claude an even more effective agent over longer time horizon tasks, and coordinate with groups of other agents at many different scales to accomplish large tasks. This team endeavors to maximize agent performance by solving challenges at whatever level is needed, whether it’s novel harness design, improved agent affordances and infrastructure, or finetuning.</p>\n<p>Given that this is a nascent field, we ask that you share with us a project built on LLMs that showcases your skill at getting them to do complex tasks. Here are some example projects of interest: design of complex agents, quantitative experiments with prompting, constructing model benchmarks, synthetic data generation, or model finetuning. There is no preferred task; we just want to see what you can build. It’s fine if several people worked on it; simply share what part of it was your contribution. You can also include a short description of the process you used or any roadblocks you hit and how to deal with them, but this is not a requirement.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Ideate, develop, and compare the performance of different agent harnesses (eg memory, context compression, communication architectures for agents)</li>\n<li>Design and implement rigorous quantitative benchmarks for large scale agentic tasks</li>\n<li>Assist with automated evaluation of Claude models and prompts across the training and product lifecycle</li>\n<li>Work with our product org to find solutions to our most vexing challenges applying agents to our products</li>\n<li>Help create and optimize data mixes for model training that maximize Claude’s performance or ease of use on agentic tasks</li>\n</ul>\n<p><strong>You may be a good fit if you:</strong></p>\n<ul>\n<li>Have experience developing complex agentic systems using LLMs</li>\n<li>Have significant software engineering and ML experience</li>\n<li>Have spent time prompting and/or building products with language models</li>\n<li>Have good communication skills and an interest in working with other researchers on difficult tasks</li>\n<li>Have a passion for making powerful technology safe and societally beneficial</li>\n<li>Stay up-to-date and informed by taking an active interest in emerging research and industry trends.</li>\n<li>Enjoy pair programming (we love to pair!)</li>\n</ul>\n<p><strong>Strong candidates may also have experience with:</strong></p>\n<ul>\n<li>Large-scale RL on language models</li>\n<li>Multi-agent systems</li>\n</ul>\n<p><strong>Representative projects:</strong></p>\n<ul>\n<li>Design and build a novel agent harness that outperforms existing agents on coding or knowledge work benchmarks</li>\n<li>Design and build agent affordances that unlock new capabilities for internal use and deployed products</li>\n<li>Design and build a novel eval that measures how many agents interact in groups to solve problems</li>\n<li>Build a scaled model evaluation framework driven by model-based evaluation techniques.</li>\n<li>Build the prompting and model orchestration for a production application backed by a language model</li>\n<li>Finetune Claude to maximize its performance using a particular set of agent tools or harness</li>\n</ul>\n<p><strong>Logistics</strong></p>\n<p><strong>Education requirements:</strong> We require at least a Bachelor&#39;s degree in a related field or equivalent experience. <strong>Location-based hybrid policy:</strong> 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.</p>\n<p><strong>Visa sponsorship:</strong> 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.</p>\n<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.</p>\n<p><strong>Your safety matters to us.</strong> 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—</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_7d5a8f0f-540","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/4017544008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$500,000 - $850,000 USD","x-skills-required":["LLMs","agent harnesses","quantitative benchmarks","automated evaluation","data mixes","model training"],"x-skills-preferred":["large-scale RL","multi-agent systems","pair programming"],"datePosted":"2026-03-08T13:44:11.238Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, Seattle, WA, New York City, NY"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"LLMs, agent harnesses, quantitative benchmarks, automated evaluation, data mixes, model training, large-scale RL, multi-agent systems, pair programming","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":500000,"maxValue":850000,"unitText":"YEAR"}}}]}