Genesis Molecular AI
ML & Molecular Simulation Scientist
San Mateo, CA · Full-time · Posted Jun 12, 2026
- Experience
- No specific number of years stated; postdoctoral or industry experience is a plus.
- Education
- PhD (preferred) in computer science, machine learning, chemical engineering, biophysics, physics, or a closely related field.
About the job
Develops and applies 3D molecular simulation and machine-learning methods to support drug discovery, from hit identification through lead optimization.
What you'll do
- Build 3D machine-learning models and combine them with physics-based approaches for molecular design, property prediction, and scoring.
- Develop and apply molecular simulation methods, including molecular dynamics, enhanced sampling, and free-energy calculations.
- Collaborate with CADD and discovery teams, contribute to the GEMS platform, and communicate scientific results.
What they ask for
- Practical experience with 3D machine learning applied to molecular data.
- Hands-on expertise in molecular simulation, including MD, enhanced sampling, and/or free-energy methods.
- Proficiency in Python and scientific computing libraries; comfort with HPC environments and scripting.
- Track record applying computational methods to scientific problems, demonstrated through publications, open-source contributions, or industry impact.
Nice to have
- Familiarity with cheminformatics and ADMET property prediction.
- Contributions to open-source simulation or ML tooling.
Tools
GROMACS, AMBER, OpenMM, NAMD, MOE, PyMOL, Python, PyTorch
AI focus
Develops and applies geometric and generative machine learning for molecular design and property prediction, integrating AI with physics-based simulation and scoring for drug discovery.
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