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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b47fc91b-597"},"title":"Anthropic Fellows Program — ML Systems & Performance","description":"<p>The Anthropic Fellows Program is a 4-month full-time research opportunity designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent, regardless of previous experience. Fellows will primarily use external infrastructure to work on an empirical project aligned with our research priorities, with the goal of producing a public output. In one of our earlier cohorts, over 80% of fellows produced papers.</p>\n<p>We run multiple cohorts of Fellows each year and review applications on a rolling basis. This application is for cohorts starting in July 2026 and beyond.</p>\n<p>As a Fellow, you will receive:</p>\n<ul>\n<li>Direct mentorship from Anthropic researchers</li>\n<li>Access to a shared workspace in either Berkeley, California or London, UK</li>\n<li>Connection to the broader AI safety and security research community</li>\n<li>A weekly stipend of $3,850 USD / £2,310 GBP / $4,300 CAD, plus benefits</li>\n<li>Funding for compute and other research expenses</li>\n</ul>\n<p>The interview process will include an initial application and reference check, technical assessments and interviews, and a research discussion.</p>\n<p>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.</p>\n<p>The expected base stipend for this role is $3,850 USD / £2,310 GBP / $4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension).</p>\n<p>Fellows will undergo a project selection and mentor matching process. Potential mentors include Alwin Peng and Zygi Straznickas. For a past example of an engineering-heavy project, see &#39;AI agents find $4.6M in blockchain smart contract exploits&#39;.</p>\n<p>Projects in this workstream may include building a CPU simulator for accelerator workloads, adding backends for different accelerators on an open source project, building on demand infrastructure for other infrastructure heavy fellows projects, and building complex synthetic data or environment pipelines.</p>\n<p>To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace locations are in London and Berkeley, and we are open to remote fellows in the UK, US, or Canada.</p>\n<p>We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organisations.</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_b47fc91b-597","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5183051008","x-work-arrangement":"remote","x-experience-level":"entry","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python programming","Software engineering","Complex ML systems","Distributed systems","High-performance computing","Training, fine-tuning, or evaluating large language models","Analyzing and debugging model training processes"],"x-skills-preferred":["Experience with training, fine-tuning, or evaluating large language models","Adept at analyzing and debugging model training processes","Strong background in a discipline relevant to a specific Fellows workstream","Experience in areas of research or engineering related to their workstream"],"datePosted":"2026-04-18T15:34:47.218Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python programming, Software engineering, Complex ML systems, Distributed systems, High-performance computing, Training, fine-tuning, or evaluating large language models, Analyzing and debugging model training processes, Experience with training, fine-tuning, or evaluating large language models, Adept at analyzing and debugging model training processes, Strong background in a discipline relevant to a specific Fellows workstream, Experience in areas of research or engineering related to their workstream"}]}