Role Overview
The Research Scientist, Life Sciences position at Anthropic in San Francisco, CA is a full-time role focused on developing Claude into an advanced life sciences research assistant. This opportunity suits professionals with a strong background in machine learning and computational biology who want to shape how frontier artificial intelligence systems approach scientific discovery.
Key Responsibilities
Build and ship agentic tools and integrations allowing Claude to execute real life science workflows such as bioinformatics pipelines, database queries, analysis notebooks, and literature reviews.
Design and construct evaluation benchmarks to measure model capabilities on biology tasks including figure interpretation, bioinformatics, protocol reasoning, and literature synthesis.
Collaborate closely with product and design teams to scope, prototype, and release features for life sciences users.
Partner with external biotech, pharma, and academic users to understand real-world workflows and transform feedback into product enhancements.
Build and maintain the engineering infrastructure supporting the biology product surface, including tool scaffolding, data pipelines, and evaluation harnesses.
Translate deep biological domain knowledge into clear product requirements and evaluation criteria to guide model improvement.
Requirements
Experience applying machine learning and software engineering to biological problems such as computational biology, bioinformatics, protein machine learning, or genomics.
Professional background in drug discovery or development within a biotech or pharmaceutical company, or fundamental research experience in an academic setting.
Strong software engineering skills with the ability to write production-quality Python, navigate large codebases, and manage infrastructure end-to-end.
Hands-on experience with training or fine-tuning machine learning models, including large language models, protein language models, or other deep learning architectures.
Demonstrated track record of shipping computational tools or pipelines utilized by biologists.
Comfort with navigating ambiguity and defining problems within a rapidly evolving research environment.
Ability to work independently while collaborating closely with research, product, and domain-expert teams.
Results-oriented mindset with a strong bias for rapid iteration and measurable impact.
Nice to Have
Five plus years of experience applying machine learning and software engineering to biological problems.
Ph.D. in computational biology, bioinformatics, bioengineering, computer science, or a related quantitative field, or equivalent industry experience.
Experience with large language model post-training methods such as reinforcement learning from human feedback, reinforcement learning from verifiable rewards, supervised fine-tuning data curation, or evaluation-driven development.
Direct experience with therapeutic discovery pipelines, including target identification, lead optimization, ADMET modeling, or clinical data analysis.
Familiarity with bioinformatics tooling and pipelines such as sequence analysis, structure prediction, single-cell analysis, and variant calling.
Experience building agentic systems or tool-use environments.
Published research in machine learning for biology or open-source contributions to computational tools.
Fluency with biological databases like UniProt, PDB, Ensembl, and NCBI, along with the ability to reason about schemas and failure modes.
Skills and Tools
Python
Large Language Models (LLMs)
Bioinformatics pipelines and tooling
Biological databases including UniProt, PDB, Ensembl, and NCBI
Machine learning infrastructure and evaluation frameworks
Salary and Benefits
Annual base salary range of $300,000 to $320,000 USD.
Competitive compensation and benefits package.
Optional equity donation matching.
Generous vacation and parental leave policies.
Flexible working hours.
Office space in San Francisco designed for collaboration.
Visa sponsorship available for qualifying candidates with support from a retained immigration lawyer.
About the Company
Anthropic is a public benefit corporation headquartered in San Francisco, California, dedicated to creating reliable, interpretable, and steerable artificial intelligence systems. The organization operates as a collaborative team of researchers, engineers, policy experts, and business leaders working on large-scale AI research. Anthropic views artificial intelligence research as an empirical science and emphasizes safety, ethical standards, and impactful scientific progress.
How to Apply
Interested candidates should submit their application directly on the official Anthropic careers page.
