Research Engineer, Pretraining Scaling - London
London, UK
Posted 16d ago
About the job
Anthropic's ML Performance and Scaling team is responsible for training our production pretrained models, a critical function that directly shapes the company's future and its mission to build safe, beneficial AI systems. As a Research Engineer on this team, you will ensure our frontier models train reliably, efficiently, and at scale. This demanding, high-impact role requires deep technical expertise and a passion for large-scale ML systems, operating at the boundary between research and engineering. You will work across the entire production training stack, including performance optimization, hardware debugging, experimental design, and launch coordination, responding to critical production issues during launches.
Responsibilities
- Own critical aspects of the production pretraining pipeline, including model operations, performance optimization, observability, and reliability.
- Debug and resolve complex issues across the full stack, from hardware and networking to training dynamics and evaluation infrastructure.
- Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance.
- Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams.
- Build and maintain production logging, monitoring dashboards, and evaluation infrastructure.
- Add new capabilities to the training codebase, such as long context support or novel architectures.
- Collaborate closely with teammates across different locations and with other specialized teams.
- Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned.
Requirements
- Hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems.
- Enjoy both research and engineering work, with a balanced interest in both.
- Excited about being on-call for production systems, working extended hours during launches, and solving hard problems under pressure.
- Ability to thrive when working on whatever is most impactful, adapting to changing production needs.
- Excel at debugging complex, ambiguous problems across multiple layers of the stack.
- Communicate clearly and collaborate effectively, especially during high-stress incidents and across time zones.
- Passionate about the work itself and dedicated to refining your craft as a research engineer.
- Care about the societal impacts of AI and responsible scaling.
Benefits
- Annual compensation range: £260,000 — £630,000 GBP