Applied ML Scientist (Staff / Principal)

About The Team

Join a world-class team at the forefront of AI and biochemistry. At Genesis Molecular AI, we’re a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases. We don’t just apply machine learning to biology; we are conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field. You will work side-by-side with top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations.

About The Role

This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines. You will act as both a translator and a strategist, ensuring our research is aimed at the most critical challenges and that our drug hunters can leverage the full power of our industry-leading AI platform.

What You’ll Do

• Work directly with project teams to assess model performance and utility, including applicability to current project needs, and collaborate with ML and engineering teams to resolve issues or add new functionality.
• Aid experimental colleagues with use and interpretation of model predictions by providing context about model quality and prediction uncertainty.
• Evaluate model quality by validating predictions against project data and internal or external benchmarks.
• Curate internal and external datasets for model training and validation (in collaboration with experimental teams).
• Contribute to design and analysis of experiments on model changes and alternative architectures.

Nice to Have’s

• A PhD in Cheminformatics, Computational Chemistry, Computer Science, or a related field.
• A track record of publications applying machine learning to drug discovery challenges.
• Deep expertise in advanced modeling techniques such as graph neural networks, multitask modeling, active learning, or Bayesian optimization.
• Experience with large-scale data management, including SQL databases and data pipelining tools.
• A strong opinion on molecule featurization and model validation.

Compensation, Benefits, And Perks

• Competitive compensation package that includes salary and equity.
• Comprehensive health benefits: Medical, Dental, and Vision (covered 100% for the employees).
• 401(k) plan.
• Open (unlimited) PTO policy.
• Free lunches and dinners at our offices.
• Paid family leave (maternity and paternity).
• Life and long- and short-term disability insurance.

About Genesis Molecular AI

Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. Our generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis is backed by premier AI and life science investors, including a16z, NVIDIA, Rock Springs Capital, Menlo Ventures, T. Rowe Price, Fidelity, and Radical Ventures. Genesis has also signed category-leading AI-pharma deals, the most recent of which was a significant expansion with Incyte (see coverage in Forbes and GEN) with a total potential deal value of several billion dollars. Genesis is headquartered in San Mateo, CA, with a fully integrated laboratory in San Diego. We are proud to be an inclusive workplace and an Equal Opportunity Employer.