Genesis Molecular AI

ML & Molecular Simulation Scientist

San Mateo, CA

Sponsorship not specifiedDetected 40 days ago

PythonMachine LearningDeep LearningPyTorchNumPyLLMsResearchCollaboration

About the role

We don't just apply machine learning to biology - we conduct 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 world-class researchers across ML, chemistry, and biology, with access to large-scale compute infrastructure and simulation pipelines, contributing to a platform where physics-based methods and AI advance together.

Integrate physics-based and ML + data-driven approaches, combining force field methods, quantum chemistry, and structure-based design with modern ML to improve accuracy and throughput
Develop and apply simulation methods spanning molecular dynamics, enhanced sampling (metadynamics, replica exchange, umbrella sampling), and free energy calculations (FEP/TI) to support active drug discovery programs
Contribute to the GEMS platform, improving our generative AI and scoring capabilities, focusing on 3D methods; strengthen ML and physics-based scoring functions (and their intersection), build next-gen force fields
Stay current with the field, implementing and adapting methods from the latest literature in geometric ML, biomolecular simulation, and computational drug design
Genesis Molecular AI http://genesis.ml is pioneering foundation models for molecular AI to unlock a new era of drug design and development.

Proficiency in Python and scientific computing libraries (PyTorch, JAX, NumPy, MDAnalysis, RDKit)
comfort with HPC environments and scripting for large-scale simulation workflows
A track record of applying computational methods to real scientific problems, demonstrated through publications, open-source contributions, or industry impact

Familiarity with cheminformatics and ADMET property prediction
Contributions to open-source simulation or ML tooling
Paid company holidays
Daily meals and snacks in the office
Contribute to the GEMS platform, improving our generative AI and scoring capabilities, focusing on 3D methods
Communicate scientific results clearly to multidisciplinary teams, including experimental chemists and biologists
postdoctoral or industry experience is a plus
Deep, hands-on expertise in molecular simulation, including MD, enhanced sampling, and/or free energy methods using tools such as GROMACS, AMBER, OpenMM, or NAMD

Highly competitive compensation including base, bonus, and equity
Comprehensive health, dental, and vision insurance (fully covered for employees)
Stock option eligibility
Open PTO policy
Flexible work environment
Build and apply ML models informed by 3D structural data, including geometric deep learning, equivariant neural networks, and diffusion-based generative models for molecular design and property prediction
At Genesis, simulation and machine learning aren't separate disciplines: they're deeply integrated, and the scientists who do this work sit at the center of everything we build.

At Genesis Molecular AI, we're a tight-knit team of deep learning researchers, computational scientists, and drug discovery pioneers united by a single mission: to develop the next generation of AI-driven therapies for patients with severe diseases.
they're deeply integrated, and the scientists who do this work sit at the center of everything we build.
We are proud to be an inclusive workplace and an

This listing is sourced directly from Genesis Molecular AI's careers page and normalized into a canonical job model.