Member of the Technical Staff, Cheminformatics

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

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.

Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator.

You 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 You

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

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

Our Values

Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions.

Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards.

Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community.

Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner.

Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling.

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