Member of the Technical Staff, Cheminformatics

Responsibilities

• Develop and train models that incorporate knowledge of chemical synthesis routes and reactions
• Build scalable computational tools to evaluate synthetic feasibility across molecular libraries
• Interpret model inputs and outputs in chemistry terms, translating between generative AI and synthesis
• Collaborate with drug discovery and model teams to prioritize candidates
• Build and maintain cheminformatics pipelines for molecular analysis and property calculation

Requirements

• PhD in chemistry, computational chemistry, cheminformatics, or related field with 2+ years post-doc/industry experience, or Master's with 5+ years experience
• Deep understanding of organic chemistry, synthetic routes, and chemical reactions
• Experience training machine learning models on molecular and chemical data
• Strong programming skills in Python and experience building computational pipelines
• Understanding of drug-like properties, medicinal chemistry, and synthetic feasibility

Preferred Qualifications

• Experience with retrosynthetic analysis or computational synthesis planning
• Experience with molecular property prediction or QSAR modeling
• Publications in top-tier venues like NeurIPS, ICML, ICLR, or relevant chemistry journals
• Drug discovery experience in hit-to-lead or lead optimization
• Experience working with generative molecular models

About the Company

Output is a stealth-mode startup building biological reasoning models that understand biology at scale. Backed by Y Combinator and top-tier VCs, the team consists of repeat founders and biotech veterans focused on generating novel therapies through AI.