Research Engineer (AI)

TL;DR

Research Engineer (AI): Developing and optimizing the next generation of large language models with an accent on model architecture, algorithms, and training infrastructure. Focus on designing scientific experiments, scaling distributed training jobs, and creating interactive visualizations of model internals.

Location: London, UK (hybrid, requiring at least 25% office presence)

Salary: £260,000–£630,000 GBP

Company

Anthropic is a public benefit corporation dedicated to creating reliable, interpretable, and steerable AI systems.

What you will do

• Conduct research and implement solutions for model architecture, algorithms, and data processing.
• Lead small research projects and collaborate with team members on larger initiatives.
• Design, run, and analyze scientific experiments to advance understanding of large language models.
• Optimize and scale training infrastructure to improve efficiency and reliability.
• Develop and improve dev tooling to enhance team productivity.
• Contribute to the entire stack, from low-level optimizations to high-level model design.

Requirements

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field.
• Strong software engineering skills with a proven track record of building complex systems.
• Expertise in Python and experience with deep learning frameworks (PyTorch preferred).
• Familiarity with large-scale machine learning, particularly in the context of language models.
• Ability to balance research goals with practical engineering constraints.
• Must be based in the UK and work from the London office at least 25% of the time.
• Visa sponsorship is available for qualified candidates.

Nice to have

• Work on high-performance, large-scale ML systems.
• Familiarity with GPUs, Kubernetes, and OS internals.
• Experience with language modeling using transformer architectures.
• Knowledge of reinforcement learning techniques.
• Background in large-scale ETL processes.

Culture & Benefits

• Work as a single cohesive team on large-scale AI research efforts.
• Value impact, advancing long-term goals of steerable, trustworthy AI.
• View AI research as an empirical science, highly collaborative group.
• Competitive compensation and benefits, optional equity donation matching.
• Generous vacation and parental leave, flexible working hours.
• Commitment to fostering a diverse and inclusive workplace.