Cheminformatics Scientist - Molecular AI & Synthesis

Output Biosciences; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Competitive salary

Equity

Medical, dental, and vision coverage

Job summary

Output Biosciences is pioneering a biological reasoning model that understands biology at scale. This role focuses on advancing the models and computational methods that optimize molecular generation for practical chemistry and synthesis.

You will train models on synthesis routes, evaluate synthetic feasibility, translate between AI outputs and chemistry, and collaborate with drug discovery teams to prioritize candidates for real-world impact.

Qualifications

• PhD or Master with relevant experience in computational chemistry or cheminformatics

Responsibilities

• Develop and train models incorporating knowledge of chemical synthesis routes and reactions to steer molecular generation toward synthetically feasible molecules
• Build scalable computational tools to evaluate synthetic feasibility across large molecular libraries
• Interpret model inputs and outputs in chemistry terms, translating between generative AI and synthesis
• Collaborate with drug discovery and model teams to bring chemistry expertise to evaluation and prioritization
• Develop and maintain cheminformatics pipelines for molecular analysis, property calculation, and candidate assessment

Skills

Python

Cheminformatics

Molecular ML

Organic chemistry

Computational pipelines

Drug-like properties

Education

PhD in chemistry or related field

Master's degree in related field

Job description

Output Biosciences is pioneering a biological reasoning model that understands biology at scale. This role focuses on advancing the models and computational methods that optimize molecular generation for practical chemistry and synthesis.

You will train models on synthesis routes, evaluate synthetic feasibility, translate between AI outputs and chemistry, and collaborate with drug discovery teams to prioritize candidates for real-world impact.