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Role description

Product Software Engineer (Senior / Staff)

Genesis Molecular AI logoGenesis Molecular AI
AI-native
TypeFull-time
WorkplaceHybrid
SeniorityStaff / Lead
LocationSan Mateo, CA
Posted10/12/2026
Engineering

Product Software Engineer (Senior / Staff)

Genesis Molecular AI is building a world-class software team to solve problems in drug discovery through machine learning, biophysical simulation, and computational chemistry. We are looking for engineers excited to help develop new medicines and play a critical role in building out our software platform.

You will

  • Own and evolve the full-stack platform that computational chemists use daily, from data exploration and experiment management to real-time visualization, shipping AI-native workflows and modern interaction patterns that shorten the loop between hypothesis and insight

  • Build tools for exploring and visualizing high-dimensional datasets containing molecules, proteins, and ML model predictions

  • Design flexible systems for running complex chemical workflows incorporating different computational chemistry tools and ML models

  • Partner with machine learning engineers and computational chemists to develop and productionize new computational methods for molecular property prediction

  • Scale our data infrastructure to handle billions of datapoints and thousands of parallel deep learning and molecular dynamics jobs

You are

  • A deep thinker who reasons from first principles, balances attention to detail with architectural thinking, and has an investigative curiosity to find the root cause of a problem

  • Comfortable owning problems across the entire stack — frontend interfaces, backend services, data pipelines, and infrastructure

  • Experienced shipping production code and driving projects end-to-end with minimal hand-holding

  • Motivated by working closely with users to understand their problems and design simple solutions

  • Excited to work at the intersection of software engineering, drug discovery, and machine learning

What we offer

  • The opportunity to work on high impact tools and products that are immediately deployed to accelerate the discovery of new medicines

  • Strong technical coworkers in AI, software, and chemistry, who all have a powerful mix of intellectual curiosity and humility. The team reads and discusses 1-2 machine learning or chemistry papers every week to stay on top of the field and inspire new ideas

  • Competitive salary and equity. Medical, dental, and vision insurance, and a 401(k) program

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.

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Company info

Genesis Molecular AI logo

Genesis Molecular AI

Genesis Molecular AI – headquartered in Burlingame, CA, with a fully integrated laboratory in San Diego and offices in New York – is pioneering foundation models for molecular AI to unlock a new era of drug design and development. We are using a proprietary state-of-the-art generative and predictive AI platform called GEMS (Genesis Exploration of Molecular Space), to accelerate and optimize small molecule drug discovery. The GEMS platform integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. GEMS accelerates hit ID through lead optimization and candidate selection by generating promising molecules for synthesis and experimental testing, and iterating this process through cycles of AI-enabled discovery and optimization. We have leveraged GEMS to build an internal pipeline with multiple programs against high-value targets, including data-poor and canonically un

Private company
HQBurlingame, United States
Size51-200 employees
Unlock human wisdom
ThesisTermsPrivacy
Industry
Biotechnology Research
Tech stackbridge, c10, macos, microsoft-forefront, elearning-lms, broadly, scaleai, workspace, slack, microsoft-powerpoint

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