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Genesis Molecular AI

AI-driven drug discovery platform for pharma

Machine Learning Research Scientist - Foundation Models

AI ResearchConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • A deep learning expert with a portfolio of novel research in one or more cutting-edge domains of generative or predictive modeling, such as diffusion, flow matching, reinforcement learning, foundation model architectures, and training methods.
  • An independent, first-principles thinker with ownership of research projects and the ability to complete them.
  • Strong coding ability and comfort working deeply in the engineering stack to build, debug, and ship models.
  • Willingness to learn in the emerging field at the intersection of artificial intelligence, physics, chemistry, and biology; prior biology or chemistry experience is not required.
  • Strong communication skills and the ability to work collaboratively in a mission-driven science and engineering environment.

Responsibilities

  • Lead transformative research projects from conception to implementation, tackling core challenges in generative modeling for molecular systems.
  • Design and develop novel models and algorithms based on literature in diffusion models, flow matching, reinforcement learning, large language models, and other advanced areas.
  • Execute experiments at scale using computational infrastructure to validate hypotheses and advance the state of the art.
  • Collaborate with a multidisciplinary team to translate research into impact on the drug discovery platform.
  • Publish research and represent Genesis at artificial intelligence and machine learning conferences and workshops.
  • Mentor and guide other researchers and engineers.

Desired Qualifications

  • PhD in machine learning, computer science, or other computational sciences, or equivalent research experience demonstrated by a strong publication record.
  • Hands-on experience with PyTorch, PyTorch Lightning, Ray Distributed Training, and PyTorch Geometric.
  • Experience with distributed training and inference of large models on graphics processing unit clusters.
  • Familiarity with molecular data, including proteins and small molecules, physics-informed machine learning, or three-dimensional point-cloud data.

About the Company

Genesis Molecular AI

AI-driven drug discovery platform for pharma

Genesis Molecular AI uses artificial intelligence to speed up drug discovery for the pharmaceutical industry. It combines 3D spatial graph modeling with molecular simulations to generate and evaluate drug candidates and identify novel protein targets. The platform translates complex molecular data into actionable candidates and predicts how they bind to targets to help partners select promising therapies. It differentiates itself by integrating 3D spatial graph modeling with simulations to explore untapped chemical space and by focusing on B2B partnerships with pharma/biotech, with notable deals such as Eli Lilly and a $200M Series B led by Andreessen Horowitz; its goal is to accelerate partner drug discovery.

Company size
51-200
Company stage
Late Stage VC
Total funding
$400.1M
Headquarters
San Mateo, CA
Founded
2019

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