{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/title/tpu-kernel-engineer"},"x-facet":{"type":"title","slug":"tpu-kernel-engineer","display":"Tpu Kernel Engineer","count":2},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_01794f13-11a"},"title":"TPU Kernel Engineer","description":"<p>As a TPU Kernel Engineer at Anthropic, 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 optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance.</p>\n<p>Strong candidates will have a track record of solving large-scale systems problems and low-level optimization. They should have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators, and be results-oriented with a bias towards flexibility and impact.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Identify and address performance issues across multiple ML systems</li>\n<li>Design and optimize kernels for the TPU</li>\n<li>Provide feedback to researchers on model changes and their impact on performance</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n<li>Bachelor&#39;s degree or equivalent combination of education, training, and/or experience</li>\n<li>Relevant field of study</li>\n<li>Years of experience required will correlate with the internal job level requirements for the position</li>\n</ul>\n<p>Benefits:</p>\n<ul>\n<li>Competitive compensation and benefits</li>\n<li>Optional equity donation matching</li>\n<li>Generous vacation and parental leave</li>\n<li>Flexible working hours</li>\n<li>Lovely office space in which to collaborate with colleagues</li>\n</ul>\n<p>Note: This job description is a rewritten version of the original ad, focusing on the key responsibilities, requirements, and benefits.</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_01794f13-11a","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/4720576008","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$280,000-$850,000 USD","x-skills-required":["ML systems optimization","TPU kernel design and optimization","Large-scale systems problem-solving","Low-level optimization","Results-oriented approach"],"x-skills-preferred":["High-performance computing","Machine learning framework internals","Language modeling with transformers","Accelerator architecture","Collective communication algorithms"],"datePosted":"2026-04-18T15:53:09.480Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA | New York City, NY | Seattle, WA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"ML systems optimization, TPU kernel design and optimization, Large-scale systems problem-solving, Low-level optimization, Results-oriented approach, High-performance computing, Machine learning framework internals, Language modeling with transformers, Accelerator architecture, Collective communication algorithms","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_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"}}}]}