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Research Engineer, Machine Learning (Reinforcement Learning)

Anthropic · London, United Kingdom

Confidence
High confidence
Posted
11 Feb 2026
First seen
25 Oct 2026
Last checked

Evidence

High confidence

The posting says Anthropic sponsors visas, and Anthropic is on the UK Home Office register.

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UK Home Office Register of Licensed Sponsors

Listed as Anthropic Limited. London · Skilled Worker route · A rating. Snapshot 26 Oct 2026.

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Job posting

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On job-boards.greenhouse.io/anthropic, read 26 Oct 2026.

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First seen 25 Oct 2026. We check every day and remove closed roles.

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job-boards.greenhouse.io/anthropic

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Being on the register means Anthropic can sponsor visas. It doesn’t confirm this role qualifies, so check with the recruiter.

About the role

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 teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.

5. Our work spans several key areas: • Developing systems that enable models to use computers effectively • Advancing code generation through reinforcement learning • Pioneering fundamental RL research for large language models • Building scalable RL infrastructure and training methodologies • Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.

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