Research Engineer, Pretraining Scaling (London) – Flexible Hours

Mat Vin; Greater London; Hybrid; GBP 260,000 - 630,000; Full time

Job summary

Anthropic in London is seeking a Research Engineer focused on Pretraining Scaling to help production pretrained models train reliably, efficiently, and at scale. You will work across the full training stack, optimize performance, and debug issues that arise during launches.

Join a collaborative team spanning SF and London, contributing to experimental design, instrumentation, and operational excellence while shaping the efficiency of large-scale ML systems for safe, beneficial AI.

Qualifications

• Bachelor’s degree or equivalent in a relevant field.
• Hands-on experience training large language models (LLMs).
• Knowledge of distributed training, observability, or ML systems.

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, 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 SF and London, as well as with Tokens, Architectures, and Systems teams
• Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned

Skills

LLM training experience

JAX

TPU

PyTorch

Distributed systems

Education

Bachelor’s degree in a relevant field

Tools

JAX

PyTorch

TPU

Job description

Anthropic in London is seeking a Research Engineer focused on Pretraining Scaling to help production pretrained models train reliably, efficiently, and at scale. You will work across the full training stack, optimize performance, and debug issues that arise during launches.

Join a collaborative team spanning SF and London, contributing to experimental design, instrumentation, and operational excellence while shaping the efficiency of large-scale ML systems for safe, beneficial AI.