Research Engineer​/Research Scientist, Biology & Life Sciences

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.

We're seeking an exceptional Research Engineer / Research Scientist to join our Life Science team  team is organized around the north star goal of accelerating progress in the life sciences, from early discovery through translation, by an order of magnitude. Our team likes to think across the whole model stack. In this role, you ll combine your deep expertise in biology with machine learning engineering to develop novel evaluation frameworks and training strategies that push the frontier of what AI can achieve in biology.

As a founding member of our team, you ll 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 ll collaborate closely with world-class researchers and engineers to build AI systems that can engage in all phases of research and development, while maintaining our commitment to safety and beneficial impact.

• Design and implement evaluation methodologies for assessing AI model capabilities relevant to biological research and applications
• Develop and execute strategies to systematically improve model performance on scientific tasks
• Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
• Collaborate with domain experts and partners to establish benchmarks and gather high-quality data
• Translate between biological domain knowledge and machine learning objectives

• Have 8+ years of machine learning experience, with demonstrated ability to train and evaluate large language models
• Have 5+ years of hands-on experience in life sciences R&D, with deep expertise in areas such as molecular biology, drug discovery, or computational biology
• Have a track record of bridging biological domain knowledge with computational approaches to solve real scientific problems
• Are proficient in Python and familiar with modern ML development practices
• Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments
• Can work independently while maintaining strong collaboration with cross-functional teams
• Are results-oriented, with a bias towards flexibility and impact
• Thrive in a fast-paced research environment where you balance rigorous scientific standards with rapid iteration
• Are passionate about using AI to accelerate scientific discovery while maintaining high ethical standards
• Have experience managing data pipelines and working with large-scale biological datasets

• Ph.D. in a biological science (molecular biology, biochemistry, computational biology), in Machine Learning, or in a related field, or equivalent industry experience
• Published research or practical experience in scientific AI applications or long-horizon reasoning
• A history working on Reinforcement Learning and/or Pretraining
• Knowledge of containerization technologies (Docker, Kubernetes) and cloud deployment at scale
• Demonstrated ability to work across multiple domains (language modeling, systems engineering, scientific computing)
• Experience with modern machine learning techniques and model training methodologies
• Familiarity with biological databases (Uni Prot, Gen Bank, PDB) and computational biology tools
• Experience in drug discovery, including computational chemistry or structure-based design
• Knowledge of regulatory requirements for therapeutic development or clinical research
• Contributions to open-source scientific software or databases

Not all strong candidates will meet every single qualification as listed. We encourage you to apply even if you do not believe you meet every single qualification. We think AI systems like the ones we re building have enormous social and ethical implications. We…