Pre-Training Research Engineer for Safe AI & LLMs

Anthropic; United States; Remote; USD 140,000 - 230,000; Full time

Job summary

Anthropic is seeking a Research Engineer to join the Pre-training team, developing the next generation of large language models. You will work at the intersection of cutting-edge research and practical engineering to build safe, steerable AI systems.

You will conduct experiments, optimize training pipelines, contribute to model architecture, and collaborate across research, engineering, and policy teams to advance scalable and reliable AI.

Qualifications

• MS or PhD in CS, ML, or related field.
• Strong software engineering with track record of building complex systems.
• Expertise in Python and deep learning frameworks (PyTorch preferred).
• Experience with large-scale ML, especially language models.
• Ability to balance research goals with engineering constraints.
• Excellent communication and collaboration.

Responsibilities

• Conduct research and implement solutions in model architecture, algorithms, data processing, and optimizer development
• Lead small research projects independently and collaborate on larger initiatives
• Design, run, and analyze experiments to advance our 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

Skills

Python

PyTorch

Software engineering

LLM knowledge

Problem solving

Communication

Education

MS or PhD in CS/ML

Tools

Docker

Kubernetes

GPUs

Job description

Anthropic is seeking a Research Engineer to join the Pre-training team, developing the next generation of large language models. You will work at the intersection of cutting-edge research and practical engineering to build safe, steerable AI systems.

You will conduct experiments, optimize training pipelines, contribute to model architecture, and collaborate across research, engineering, and policy teams to advance scalable and reliable AI.