Research Engineer, Pretraining Scaling - London
Anthropic · 🇬🇧 London, United Kingdom
Sponsorship Verification Proof
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
- Backend
- Last verified
- 2026-10-25
- First indexed
- 2026-10-25
- Posted date
- 2025-09-30
- 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 Role: Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: • Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability • Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure • Design and run experiments to improve training efficiency,…
Excerpt only — read the full requirements and apply directly on Anthropic's career page. We do not process applications.