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.

About the Role

We're seeking an exceptional Research Engineer / Research Scientist to join our Life Science team at Anthropic. Our 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.

Responsibilities:

• 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

You may be a good fit if you:

• 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

Strong candidates may have:

• 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 (UniProt, GenBank, 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

This role offers a unique opportunity to shape how AI transforms biological research. You'll work with some of the world's best AI researchers while tackling problems that matter deeply for human health and scientific understanding. If you're excited about using your expertise to guide the development of transformative AI systems, we want to hear from you.

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process