Member of the Technical Staff, Cheminformatics

About the role

The Role Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one.

Responsibilities

• Accelerate the path from a generated molecule to a synthesized compound.
• Continue building the models and computational methods that optimize Output's molecular generation for practical chemistry.
• Develop and train models that incorporate knowledge of chemical synthesis routes and reactions, steering molecular generation toward molecules that are efficient to synthesize.
• Build scalable computational tools and methods that evaluate synthetic feasibility across generated molecular libraries, systematically and at scale.
• Interpret model inputs and outputs in chemistry terms, translating between the language of generative AI and the language of synthesis.
• Work with the drug discovery and model teams, bringing chemistry expertise to molecular evaluation and candidate prioritization.
• Build and maintain cheminformatics pipelines for molecular analysis, property calculation, and candidate assessment.

Requirements

• You have a PhD in chemistry, computational chemistry, cheminformatics, or a related field with 2+ years of post-doctoral or industry research experience, or a Master's degree with 5+ years of hands-on experience in computational chemistry or cheminformatics.
• You have deep understanding of organic chemistry, synthetic routes, and chemical reactions.
• You have experience training machine learning models on molecular and chemical data, including generative models for chemistry applications.
• You have strong programming skills in Python, with experience building computational pipelines for molecular analysis.
• You understand drug-like properties and medicinal chemistry principles, and how molecular structure relates to biological activity and synthetic feasibility.
• You are comfortable working at the boundary of chemistry and machine learning, translating constraints and insights between the two.

Qualifications

• You have experience with retrosynthetic analysis or computational synthesis planning.
• You have experience with molecular property prediction or QSAR modeling.
• You have publications at top-tier venues (e.g., NeurIPS, ICML, ICLR) or relevant chemistry and cheminformatics journals.
• You have drug discovery experience, particularly in hit-to-lead or lead optimization.
• You have experience evaluating or working with generative molecular models.

Skills

• Strong programming skills in Python, with experience building computational pipelines for molecular analysis.
• Understanding of drug-like properties and medicinal chemistry principles.
• Experience with retrosynthetic analysis or computational synthesis planning.
• Experience with molecular property prediction or QSAR modeling.
• Experience with drug discovery, particularly in hit-to-lead or lead optimization.
• Experience with generative molecular models.

Benefits

• Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you.
• Competitive salary and equity in a growing, well-funded startup.
• Excellent medical, dental, and vision coverage.

Pay

Competitive salary and equity in a growing, well-funded startup.

Schedule

Flexible schedule to accommodate the needs of a dynamic and fast-paced startup environment.