The RoleYou accelerate the path from a generated molecule to a synthesized compound. This role continues to build the models and computational methods that optimize Output's molecular generation for practical chemistry.
- You will continue developing and training models that incorporate knowledge of chemical synthesis routes and reactions, steering molecular generation toward molecules that are efficient to synthesize
- You will build scalable computational tools and methods that evaluate synthetic feasibility across generated molecular libraries, systematically and at scale
- You will interpret model inputs and outputs in chemistry terms, translating between the language of generative AI and the language of synthesis
- You will work with the drug discovery and model teams, bringing chemistry expertise to molecular evaluation and candidate prioritization
- You will build and maintain cheminformatics pipelines for molecular analysis, property calculation, and candidate assessment
About YouYou 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
Bonus Points- 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
What We Offer- We encourage new and different ideas, creativity and contrarian thinking
- 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
- You own your day-to-day management. What we care about is that we all hit our milestones
- Competitive salary and equity in a growing, well-funded startup
- Excellent medical, dental, and vision coverage
