Senior/Staff Fullstack Software Engineer
genesis-molecular-ai · San Mateo
Job description
About the role
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.
Key responsibilities
- 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 and expand tools for visualizing molecules and proteins, analyzing ML models, and managing complex chemical workflows.
- 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.
Required profile
- 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.
- 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 read and discuss 1‑2 machine‑learning or chemistry papers each week.
- Competitive salary and equity, medical, dental, and vision insurance, and a 401(k) program.
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Published 2 hours ago
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genesis-molecular-ai
San Mateo
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