Primary record

Research Engineer/Research Scientist, Pre-training

Anthropic Indexed employerRemote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY · Boston, Massachusetts, United States · New York, New York, United States · San Francisco, California, United States · Seattle, Washington, United States
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Workplace

hybrid

Employment

Internship

Published

Aug 11, 2026

Closes

No date supplied

The role

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

Key Responsibilities:

• Conduct research and implement solutions in areas such as 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 our understanding of large language models

• Optimize and scale our 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

Qualifications:

• 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 l

Requirements

Department: AI Research & Engineering