Fullstack Software Engineer

Freeman Investment Company, L.P.
San Mateo, CA, United States
1 day ago
Apply on startup.jobs
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Data Analysis Computer Simulation Data Infrastructure Machine Learning Software Engineering Deep Learning Backend Production Code Front End Software Development Data Pipelines

Job description

  • 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

Requirements

  • 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

Benefits & conditions

  • 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 the company

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., 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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on startup.jobs
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:38 min

Structuring engineering efforts for hard scientific problems

Christian Nagel Christian Nagel +3 · World Congress 2026 Europe

1:52 min

Structuring and scaling the backend engineering team

Stefan Lingler Stefan Lingler +1 · Coffee With Developers

1:48 min

Automating exploratory data analysis within training pipelines

Dora Petrella · World Congress 2023

1:25 min

Distinguishing artificial intelligence from deep learning

Sam Witteveen · Coffee With Developers

2:07 min

Embracing the role of an ambitious software finisher

Seth Webster Seth Webster · World Congress 2026 Europe

1:12 min

Choosing TypeScript for complex backend applications

Maximilian Otto Maximilian Otto · World Congress 2024

Videos

See all

Related articles

See all