Research Engineer, Life Sciences

Anthropic•San Francisco, CA

1d•$350,000 - $500,000•Hybrid

About The Position

Anthropic is seeking an exceptional Research Engineer to join its Life Sciences team. The team's goal is to accelerate progress in the life sciences by an order of magnitude, from early discovery through translation. In this role, you will combine deep expertise in machine learning engineering to develop novel evaluation frameworks and training strategies that push the frontier of what AI can achieve in biology. You will work at the intersection of cutting-edge AI and the biological sciences, developing rigorous methods to measure and improve model performance on complex scientific tasks. You will collaborate closely with world-class researchers and engineers to build AI systems that can engage in all phases of research and development, while maintaining Anthropic's commitment to safety and beneficial impact. Previous experience in life sciences is welcome, but not required.

Requirements

Demonstrated experience training and evaluating large language models
Proficiency in Python and familiarity with modern ML development practices
Experience building and managing data pipelines for large-scale datasets
Comfortable navigating ambiguity and developing solutions in rapidly evolving research environments
Strong written and verbal communication skills, with the ability to work independently while collaborating effectively across cross-functional teams

Nice To Haves

8+ years of machine learning experience
Prior work experience in AI and biology, including graduate studies (molecular biology, biochemistry, computational biology, or related fields)
Experience working with large-scale biological datasets
Published research or practical experience in scientific AI applications or long-horizon reasoning
Background in reinforcement learning and/or pretraining
Knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud deployment at scale
Demonstrated ability to work across multiple domains, such as language modeling, systems engineering, and scientific computing
Contributions to open-source scientific software or databases

Responsibilities

Develop novel evaluation frameworks and training strategies that push the frontier of what AI can achieve in biology.
Work at the intersection of cutting-edge AI and the biological sciences.
Develop rigorous methods to measure and improve model performance on complex scientific tasks.
Collaborate closely with world-class researchers and engineers to build AI systems that can engage in all phases of research and development.
Maintain Anthropic's commitment to safety and beneficial impact.