Research Engineer: Safe, Steerable AI & LLM Pretraining

anthropic; Greater London; Hybrid; GBP 260.000 - 630.000; Vollzeit

Benefits dieser Stelle

Flexible working hours

Generous vacation

Zusammenfassung

Anthropic is seeking a Research Engineer to join the Pretraining team, contributing to the development of safe, steerable, and trustworthy AI systems. You will conduct research across model architecture, data processing, and training optimization, while leading small projects and collaborating with engineers and policy experts.

The role emphasizes strong Python and PyTorch experience, large-scale ML familiarity, and a passion for AI safety and societal impact.

Qualifikationen

• Advanced degree in Computer Science, Machine Learning, or related field.
• Strong software engineering skills with a track record of building complex systems.
• Experience with Python and deep learning frameworks (PyTorch preferred).
• Familiarity with large-scale ML, especially language models.
• Ability to balance research goals with engineering constraints.
• Strong problem-solving and communication skills.
• Interest in societal impacts of AI research.

Aufgaben

• Conduct research and implement model architecture, algorithms, data processing, and optimizer development.
• Lead small research projects and collaborate on larger initiatives.
• Design, run, and analyze experiments on large language models.
• Scale and optimize training infrastructure for efficiency and reliability.
• Develop and improve dev tooling to boost team productivity.
• Contribute across the stack from low-level optimizations to high-level model design.

Kenntnisse

Python

Deep learning

Research leadership

Communication skills

Problem solving

Large-scale ML

Team collaboration

Ausbildung

MS or PhD in CS/ML

Tools

GPUs

Kubernetes

OS internals

ETL pipelines

Jobbeschreibung

Anthropic is seeking a Research Engineer to join the Pretraining team, contributing to the development of safe, steerable, and trustworthy AI systems. You will conduct research across model architecture, data processing, and training optimization, while leading small projects and collaborating with engineers and policy experts.

The role emphasizes strong Python and PyTorch experience, large-scale ML familiarity, and a passion for AI safety and societal impact.