Hybrid Research Engineer: Build Safe, Scalable AI

Aimlroles; Northern (KY); Hybrid; USD 350,000 - 850,000; Full time

Job summary

Anthropic is seeking a Research Engineer to join the Pre-training team, focusing on the next generation of large language models. The role blends rigorous research with practical engineering to build safe, steerable AI systems and scalable training infrastructure.

Qualified candidates hold an MS or PhD in a related field, possess strong Python and PyTorch expertise, and can balance ambitious research with engineering pragmatism.

Qualifications

• Advanced degree (MS or PhD) in Computer Science, ML, or related field.
• Strong software engineering skills with a track record of building complex systems.
• Expertise in Python and deep learning frameworks (PyTorch preferred).
• Familiarity with large-scale ML, particularly in language models.
• Ability to balance research goals with engineering constraints.
• Strong problem-solving and communication skills.
• Commitment to societal impacts of your work.

Responsibilities

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

Skills

Strong software engineering

Python

PyTorch

Large-scale ML systems

Problem solving

Education

MS or PhD in Computer Science, Machine Learning, or related field

Tools

Python

PyTorch

Job description

Anthropic is seeking a Research Engineer to join the Pre-training team, focusing on the next generation of large language models. The role blends rigorous research with practical engineering to build safe, steerable AI systems and scalable training infrastructure.

Qualified candidates hold an MS or PhD in a related field, possess strong Python and PyTorch expertise, and can balance ambitious research with engineering pragmatism.