Founding Scientist, Cheminformatics

Founding Scientist, Cheminformatics
Internal title: Member of Technical Staff
San Francisco Bay Area (On Site)
Salary: up to $250K Generous Equity Benefits

Looking for a role that combines deep technical work with meaningful client interaction? Most scientists have to choose between advancing the science and working with customers. Here's your chance to do both.

The Company

The company are on a mission to fundamentally transform how scientific discovery happens. Every year, the life sciences industry spends over $12Bn on toxicity testing alone – tests that are slow, expensive, and often involve animal studies. We can do better.

By replacing traditional lab experiments with powerful AI predictions, we're not just saving time and money – we're accelerating the development of life-changing drugs, sustainable foods, revolutionary crops (plus so much more).

Founded in 2023, the company are already working with leading names in the pharmaceutical industry, with ambitious growth plans for 2025 and beyond.

Your Impact

You'll wear two equally important hats:

Hat #1 - Drive customer drug programs forward

• Analyze AI/ML predictions on customer's chemistry to drive towards decisions on next steps
• Deliver modeling performance, analysis of customer data, and how to interpret the results of AI/ML directly to scientific customers
• Drive the design and development of the platform based on customer needs and novel ideas you discover interacting with customers
• Work at the intersection of chemistry, biology, and product design to push the technology forward
• Have a tangible impact on the success of 100s of drug programs and influence many of the world’s best drug hunters

Hat #2 - Lead platform research & development

• Research novel machine learning representations of chemistry which make drastic improvements on SOTA
• Lead experimental design and execution of hypotheses to improve the core chemistry models
• Creating new methods to interpret model predictions and generate novel chemistry which matches customer needs
• Develop new evaluations for the model which measure its utility for customers
• Improving the foundational processing of molecular data (stereochemistry, ionization, tautomerization) and how its used in the product

You'll Thrive If You:

• Have deep chemistry knowledge, with experience across the design-make-test-analyse (DMTA) cycle of drug discovery
• Can communicate effectively with wet-lab and dry-lab scientists and engineers alike, and love to bridge the gap between different domains
• Have experience in applying AI/ML to drug discovery and see this as the future
• Love building relationships with scientific customers

Your Toolkit:

• Python ecosystem (numpy, pandas)
• Cheminformatics libraries (RDKit, datamol)
• Data processing tools (SQL, cloud computing)
• Scientific computing and visualization
• Presentation and communication skills

What's In It For You?

• Competitive Salary: Up to $250K, based on experience
• Founding Team Equity: Share significantly in the company’s success
• Direct Impact: See your work accelerate real drug discovery programs
• Growth Opportunity: Grow with the company as they scale, you might see yourself as a future leader
• Unique Career Path: Develop both technical and client-facing expertise

Interview Process:

We believe in a straightforward, transparent interview process that typically takes 2-3 weeks:

• Initial Conversation – Chat with me about your experience and aspirations, while learning more about the role and company
• CEO Meeting – Deep dive with your future manager; the conversation will focus on your technical experience as well as culture fit. Take your opportunity to as many questions as you can, it’s a two-way process after all. (30-45min)
• Technical Assessment – 30-minute technical discussion with a Co-Founder, followed by a coding test (Python).
• On-Site - Meet the founding team, present relevant research you're passionate about, and experience the collaborative culture firsthand

Keywords: Cheminformatics, Computational Chemistry, Medicinal Chemistry, Machine Learning, Deep Learning, Artificial Intelligence, AI, Chemistry, Property Prediction, Toxicity, Drug Discovery, Drug Development