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ML / AIGreenhouse job board

Research Engineer, Machine Learning (Reinforcement Learning)

Anthropic · 🇬🇧 London, United Kingdom

Sponsorship Verification Proof

✓ 🇬🇧 UK Home Office Licensed Sponsor

Employer is on the UK Home Office register of licensed sponsors.

UK Home Office Register of Licensed Sponsors (Skilled Worker route): listed as 'Anthropic Limited', London — Skilled Worker; Worker (A rating)

An official government register match confirms the employer holds an active sponsor licence in this country. It does not guarantee that every individual role meets minimum salary or skill thresholds — always confirm sponsorship eligibility with the recruiter.

The job posting also states: “Visa sponsorship: We do sponsor visas!”

Verification category
Employer on official sponsor register
Role category
ML / AI
Last verified
2026-10-25
First indexed
2026-10-25
Posted date
2026-02-11
ATS / Feed source
Greenhouse job board

Role Description (Excerpt)

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. About the…

Excerpt only — read the full requirements and apply directly on Anthropic's career page. We do not process applications.