---
title: 'Applied ML Scientist (Staff / Principal) at Genesis Molecular AI'
canonical: 'https://feeny.ai/job/applied-ml-scientist-staff-principal-genesis-molecular-ai-san-mateo-ypytjf6pxab2'
type: 'job'
last_seen: '2026-09-07'
---

# Applied ML Scientist (Staff / Principal) at Genesis Molecular AI

- **Company:** Genesis Molecular AI
- **Location:** San Mateo, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-05-19
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/genesis-molecular-ai/b239a6b5-40f2-41fd-93e6-3b7ca2c7eac7

## Job description

## About the Team

Join a world-class team at the forefront of AI and biochemistry.

At Genesis Molecular AI, we’re a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases.

We don’t just apply machine learning to biology; we are conducting 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 top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations.

## About the Role

This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines.

You will act as both a translator and a strategist, ensuring our research is aimed at the most critical challenges and that our drug hunters can leverage the full power of our industry-leading AI platform. This role requires a deep understanding of cheminformatics, computational chemistry, and experimental techniques, strong data science skills, and a talent for communicating complex ideas to a diverse, multidisciplinary team.

Positions are available at various levels of seniority: Senior, Staff, and Principal.

## What You’ll Do

- Work directly with project teams to assess model performance and utility, including applicability to current project needs, and collaborate with ML and engineering teams to resolve issues or add new functionality.
- Assist experimental colleagues with use and interpretation of model predictions by providing context about model quality and prediction uncertainty.
- Evaluate model quality by validating predictions against project data and internal or external benchmarks.
- Curate internal and external datasets for model training and validation (in collaboration with experimental teams).
- Contribute to design and analysis of experiments on model changes and alternative architectures.

You are

- A seasoned computational scientist with a proven track record of machine learning based methods to impact small molecule drug discovery projects.
- A cheminformatics expert, fluent in the language of molecular data with hands-on mastery of tools like RDKit or OpenEye.
- A scientist who speaks the language of experimental drug discovery, with a strong familiarity with common assay types (biochemical/binding/cell-based assays, in vivo studies, etc.) and CADD workflows (docking, virtual screening, ADME prediction, etc.).
- A rigorous data scientist, with experience inmodeling and analysis of small molecule datasets and passion for statistical validation, uncertainty quantification, and deriving clear insights from complex, noisy data.
- A hands-on applied scientist and software engineer with strong coding skills in Python and a deep practical knowledge of the applied ML toolkit (e.g., scikit-learn, PyTorch).
- An exceptional communicator and collaborator, able to act as the bridge between machine learning researchers and experimental scientists.
- A curious, problem-oriented mind, excited to dive into the emerging field at the intersection of AI, physics, chemistry, and biology and make foundational contributions and discoveries.
- A true team player who thrives in highly collaborative, mission-driven environments where science and engineering are deeply intertwined.
- Inspired by our culture of intellectual curiosity and the shared belief that breakthroughs happen when diverse perspectives and minds unite.

## Nice to have's

- A PhD in Cheminformatics, Computational Chemistry, Computer Science, or a related field.A track record of publications applying machine learning to drug discovery challenges.
- Deep expertise in advanced modeling techniques such as graph neural networks, multitask modeling, active learning, or Bayesian optimization.
- Experience with large-scale data management, including SQL databases and data pipelining tools.
- Strong opinions on molecule featurization and model validation.

Compensation, Benefits, and Perks

- Competitive compensation package that includes salary and equity.
- Comprehensive health benefits: Medical, Dental, and Vision (covered 100% for the employees).
- 401(k) plan.
- Open (unlimited) PTO policy.
- Free lunches and dinners at our offices.
- Paid family leave (maternity and paternity).
- Life and long- and short-term disability insurance.

## About Genesis Molecular AI

Genesis Molecular AI http://genesis.ml 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 https://www.businesswire.com/news/home/20251028030745/en/Genesis-Molecular-AI-Unveils-Pearl-a-Field-Leading-Foundation-Model-that-Achieves-Unprecedented-Performance-in-Drug-Protein-Structure-Prediction 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 https://www.forbes.com/sites/innovationrx/2026/05/20/inside-incytes-120-million-ai-for-drug-development-deal/ and GEN https://www.genengnews.com/topics/artificial-intelligence/small-molecules-to-big-partnership-incyte-genesis-expand-ai-collaboration-to-1b/) 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.

## About Genesis Molecular AI

## Company Overview
- **One-liner**: Genesis Molecular AI combines frontier AI research with deep drug discovery expertise to develop a proprietary platform (GEMS) that accelerates the design and optimization of small molecule medicines.
- **Entity Type**: Private (Series B; raised over $300M in total funding)
- **Headquarters**: Burlingame, California, United States (with a fully integrated laboratory in San Diego and offices in New York)
- **Founded**: Not publicly disclosed (first major funding round – $200M Series B – closed in 2023)
- **Founders**: Evan Feinberg Ph.D. (CEO, Co-founder) and Sergey Edunov (Co-founder); other key leaders include Will McCarthy (CTO) and Shifeng Pan Ph.D. (COO)

## Core Business
- **Primary Industry**: Biotechnology – AI-powered small molecule drug discovery.
- **Target Customers**: Large pharmaceutical partners (B2B) via platform collaborations, plus an internal pipeline of wholly owned drug programs.
- **Mission/Purpose**: “Solving the hardest problems in drug discovery to change the landscape of medicine” by creating and scaling domain-specific AI models that integrate physics, chemistry, biology, and software.

## Products & Services
- **[GEMS Platform](https://www.genesis.ml/)**: An AI operating system for molecular design. GEMS (Genesis Exploration of Molecular Space) integrates generative and predictive models to accelerate hit identification, lead optimization, and candidate selection. It is deployed for internal pipeline programs and major pharma collaborations.
- **[Pearl Foundation Model](https://www.genesis.ml/about)**: A generative foundation model for biomolecular structure prediction (protein-ligand) that demonstrated field-leading performance. Built in collaboration with NVIDIA and trained on large-scale synthetic data.
- **Internal Drug Pipeline**: Small molecule inhibitors targeting oncology (e.g., pan-mutant allosteric PIK3CA inhibitors) and immunology (e.g., inflammatory signaling pathways). Programs are in discovery stage approaching development candidate nomination.
- **Platform Partnership Model**: “Forward-deployed engineers and scientists” work alongside pharma partners (Gilead, Incyte) to apply GEMS to their targets, with deal structures that include upfront payments, milestones, and data sharing that feeds back into model training.

## Market Standing
- **Valuation/Market Cap**: Not disclosed.
- **Key Metric**: Total funding raised >$300M (including $200M Series B in 2023 co-led by a16z, with participation from Fidelity, BlackRock, NVIDIA’s NVentures, Rock Springs Capital, T. Rowe Price, Radical Ventures, Menlo Ventures).
- **Notable Investors/Partners**: Andreessen Horowitz, Fidelity, BlackRock, NVIDIA (NVentures), Rock Springs Capital, T. Rowe Price, Radical Ventures, Menlo Ventures. Pharma partners: Gilead ($35M upfront, 2024), Incyte ($150M total upfront including equity investment, 2025–2026).
- **Growth Signals**: 125 employees (+26.4% YoY); operates in 7 countries; LinkedIn following grew 41.9% in the past year; Pearl model launched to strong benchmarking results; Incyte expanded collaboration with at least 5 additional targets and data for model training.

## Competitive Advantages
- **Integration of disciplines**: The company pairs leading AI researchers with world-class drug hunters, co-creating models and medicines in iterative loops.
- **Wet-lab flywheel**: In-house lab in San Diego generates experimental data that closes the loop for model training, prediction, and validation – a virtuous cycle that strengthens the platform with every program.
- **Partnership data advantage**: Deals with Gilead and Incyte provide significant proprietary experimental data (e.g., Incyte data for training GEMS), creating a moat that is hard for pure-play AI companies to replicate.
- **Domain-specific foundation models**: Models like Pearl are purpose-built for small molecule drug discovery, unlike general-purpose generative AI.

## Strategic Focus
- **Advancing internal pipeline**: Moving lead programs in oncology (PIK3CA, apoptosis) and immunology toward development candidate nomination.
- **Scaling platform partnerships**: Expanding existing collaborations and signing new ones to broaden the impact of GEMS and generate more training data.
- **Continuous model improvement**: Investing in next-generation foundation models (e.g., Pearl) and leveraging partner data to stay at the frontier of molecular AI.
- **Hiring across AI and drug discovery**: Open roles for machine learning research scientists, software engineers, computational chemists, medicinal chemists, and biologists indicate a focus on scaling both the tech and biology teams.

## Why Work Here
- **Culture**: Described as a “meritocracy of ideas” where the strongest ideas win through evidence and reasoning, not hierarchy. Values include ownership, experimentation, candor with kindness, curiosity, and collaboration across disciplines.
- **Work Environment**: Flexible work environment with offices in Burlingame, San Diego, and New York. Daily meals and snacks provided in the office. Ergonomic consulting and equipment available.
- **Compensation & Benefits**: Highly competitive compensation including base salary, bonus, and equity. Comprehensive health, dental, and vision insurance. Open PTO policy, parental leave, 401(k) retirement savings, financial planning resources.
- **Impact**: Employees work on some of the hardest problems in drug discovery – applying cutting-edge AI to targets that are canonically undruggable, with the potential to create new treatment options for severe diseases.
- **Team Composition**: The company actively hires across AI research, software engineering, molecular simulation, and drug discovery disciplines, fostering an interdisciplinary environment where researchers and drug hunters co-create daily.

## Sources
1. [genesis.ml](https://www.genesis.ml/)
2. [genesis.ml/about](https://www.genesis.ml/about)
3. [genesis.ml/careers](https://www.genesis.ml/careers)
4. [genesis.ml/partners-pipeline](https://www.genesis.ml/partners-pipeline)
5. [LinkedIn - Genesis Molecular AI](https://www.linkedin.com/company/genesis-molecular-ai)

## Other roles at Genesis Molecular AI

- [Contract Recruiting Coordinator](https://feeny.ai/job/contract-recruiting-coordinator-genesis-molecular-ai-new-york-jp3t2jz8ff95) — New York, NY / San Francisco, CA
- [Manager, New Product Planning](https://feeny.ai/job/manager-new-product-planning-genesis-molecular-ai-san-diego-s9gybtg3hfg8) — San Diego, CA
- [ML & Molecular Simulation Scientist](https://feeny.ai/job/ml-molecular-simulation-scientist-genesis-molecular-ai-san-mateo-z7qx94p0vrzb) — San Mateo, CA
- [Staff Technical Recruiter](https://feeny.ai/job/staff-technical-recruiter-genesis-molecular-ai-san-mateo-t76m4py49wex) — San Mateo, CA
- [Fullstack Software Engineer (Senior / Staff)](https://feeny.ai/job/fullstack-software-engineer-senior-staff-genesis-molecular-ai-san-mateo-pap6516adm11) — San Mateo, CA
- [Software Engineer - Core Infrastructure](https://feeny.ai/job/software-engineer-core-infrastructure-genesis-molecular-ai-san-mateo-sgbtcj4j76d4) — San Mateo, CA
- [Machine Learning Infrastructure Engineer](https://feeny.ai/job/machine-learning-infrastructure-engineer-genesis-molecular-ai-san-mateo-a012z1zdp33y) — San Mateo, CA
- [Product Management Lead](https://feeny.ai/job/product-management-lead-genesis-molecular-ai-san-mateo-qv16q5s8c4q2) — San Mateo, CA
- [ML Research Scientist, Foundation Models (Senior / Staff / Principal)](https://feeny.ai/job/ml-research-scientist-foundation-models-senior-staff-principal-genesis-gnpr61e1bf7n) — San Mateo, CA
- [ML Research Engineer, Foundation Models (Senior / Staff / Principal)](https://feeny.ai/job/ml-research-engineer-foundation-models-senior-staff-principal-genesis-molecular-7ky449yvkh2y) — San Mateo, CA