Bloom Life Science | Founding ML Researcher (Chemistry)

Founding Machine Learning Researcher (Chemistry)San Francisco Bay Area - on-site$150 - 250K Are you an exceptional ML engineer looking to build something revolutionary?With the life science industry spending over $12Bn a year on toxicology assessments alone. What if lab experiments could be shifted to in silico? How about if we could get better results, faster and at a fraction of the current spend?The CompanyThe 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 shifting traditional lab experiments to 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 ImpactYour deep understanding of chemical structures, properties, and reactions will be crucial as you develop models that can predict molecular behavior with unprecedented accuracy. As a member of the founding team, you'll bridge the gap between complex chemistry concepts and cutting-edge AI.You're not just joining as a senior researcher - you're joining as a founding member with the equity, influence, and ownership to match. Your unique blend of chemistry insight and ML expertise will help shape the company's technical strategy from day oneWhy This Role Is DifferentYou'll own critical technical decisions from day one. This isn't about maintaining existing systems - you'll architect and build the company's core AI platform from the ground up.You'll work with unique, in-house data. No more dealing with messy public datasets. You will have access to our own high-quality data, giving you the foundation to build truly groundbreaking models.You'll see your work make a real difference. Your models won't sit in research papers - they'll be used by scientists to accelerate real-world discoveries.You'll Thrive If You:Love building complex ML systems and seeing them work in productionHave deep expertise in PyTorch and modern ML infrastructureGet excited about graph neural networks, self-supervised learning, or molecular property predictionWant to work directly with scientists and see your models drive scientific decisionsHave a strong grasp of chemistry in a drug discovery setting, and have worked with biochemical data beforeAre ready to take ownership and help shape a company's technical directionTech Stack: You'll be familiar with the following tools and technologies:PyTorch for model developmentVision transformers & graph neural networksCloud infrastructure (AWSGCP) for training at scaleModern MLOps tools (Ray, W&B)Molecular modeling libraries (RDKit)What's In It For You?Competitive Salary: Up to $250K, based on experienceFounding Team Equity: Share significantly in the company's successDirect Impact: See your work accelerate real drug discovery programsGrowth Opportunity: Grow with the company as they scaleBuild Something: Gain the experience of building a deep tech company from the ground upInterview 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 companyCEO Meeting - Intro call 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.Technical Assessment - Technical deep dive with a senior team member, followed by a take-home coding exercise (Python)On-Site - Meet the founding team, present relevant research you're passionate about, and experience the collaborative culture firsthandHit apply or reach out to me at or 857-370-5757 if you'd like to stand out and speak with me directly.Keywords: Machine Learning, Deep Learning, Artificial Intelligence, AI, Chemistry, Property Prediction, Toxicity, Graph Neural Networks, GNN, Drug Discovery, Drug Development

Created: 2025-01-09