---
title: 'Product Management Lead at Genesis Molecular AI'
canonical: 'https://feeny.ai/job/product-management-lead-genesis-molecular-ai-san-mateo-qv16q5s8c4q2'
type: 'job'
last_seen: '2026-09-07'
---

# Product Management Lead at Genesis Molecular AI

- **Company:** Genesis Molecular AI
- **Location:** San Mateo, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2025-08-13
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/genesis-molecular-ai/a8dc28d6-2f1a-471b-bdb5-6e1d982c301f

## Job description

Genesis Molecular AI is pioneering a transformative approach to drug discovery by leveraging state-of-the-art machine learning, computational chemistry, and biology. Our mission is to accelerate the development of life-changing therapies by merging cutting-edge technology with innovative science. We are building a world-class team to drive forward the future of drug discovery.

About the Team:

We are a mission-driven group of scientists and engineers using cutting-edge computational methods to discover drugs for unmet medical needs. Our work spans machine learning, computational chemistry, biology, and wet lab experimentation, all operating within a high-trust, deeply technical environment.

You’ll join a team with extremely strong ML talent that is actively pushing the frontier of AI in drug discovery. We are refining how experimental data, biological context, and computational models integrate into a seamless feedback loop.

You will help reshape how data flows from experiment → infrastructure → model → decision and increase the speed and scale at which we learn.

## The Role

This is a builder–integrator role inside a deeply technical, cross-domain environment spanning AI/ML, engineering, computational chemistry, biology, and wet lab operations. You will serve as the connective tissue and acceleration engine across these domains.

You will work closely with senior leadership to own roadmap definition and execution across critical internal platforms while driving structural improvements in how our teams operate.

This role exists to:

- Bridge domain silos and reduce friction between ML experimentation and biological context
- Operate at both the strategic systems level and the fiddly operational detail level
- Get hands dirty when needed
- Close the AI ↔ Chem loop so lab data is captured in standardized form, accessible for model training, and drives measurable model performance improvements
- Increase iteration speed by an order of magnitude from research idea to validated result
- Standardize execution across programs so we can scale programs without reinventing workflows

The products you’ll work on include:

- Nucleus, our internal platform that houses the GEMS AI system that enables all of our drug discovery programs.
- Our computational methods research platform – the data, analysis and pipelining platform that powers new physics and AI methods development.
- You will own the product roadmap, prioritize initiatives, and drive the execution of projects that support our mission to revolutionize drug discovery.

## Responsibilities

- Roadmap Ownership: Define, maintain, and communicate the technical and scientific product roadmap in alignment with company goals, ensuring prioritization of impactful projects.
- User research and design: Deeply understand user needs, translate workflow complexity into simple and effective product design.
- Team Collaboration and Translating Across Domains: Facilitate effective collaboration among software engineers, ML researchers, and computational chemistry scientists, acting as a glue to bridge technical and scientific perspectives.
- Stakeholder Engagement: Act as the primary point of contact for internal stakeholders, gathering input and communicating progress effectively.
- Data-Driven Decision Making: Leverage data and feedback to make informed decisions and iterate on product features.
- Product Strategy: Translate company objectives into actionable product plans, ensuring alignment with user needs and strategic goals.
- Execution Leadership: Drive projects from concept to completion, ensuring high-quality deliverables on time and within scope.
- Risk Management: Identify potential risks in product development and proactively implement mitigation strategies.

Within 12 months, success in this role should look like:

- A functionally closed AI ↔ Chem loop
- Measurable performance gains from internal data
- Faster model–lab feedback cycles
- Standardized, scalable execution playbooks replacing heavy customization
- Direct contribution to major method launches by bridging scientific insight and product execution

Who you are:

- 5+ years of product management experience in a technical or scientific environment
- Bachelor’s degree in Computer Science, Engineering, Chemistry, or related field (advanced degree preferred)
- Strong understanding of machine learning systems and data infrastructure
- Literacy in drug discovery, structural biology, or computational chemistry
- Proven ability to operate at the interface of ML and life sciences
- Demonstrated experience translating computational results into actionable scientific outcomes
- Experience leading complex, cross-functional initiatives
- Mindset: Passionate about innovation, problem-solving, and making a tangible impact on human health.

You are someone who:

- Runs toward ambiguity rather than away from it
- Knows what you don’t know and does not bluff in technical domains
- Thinks in systems and anticipates what will not scale
- Balances strategic thinking with hands-on execution
- Is motivated by advancing methods that impact real patients

*Experience in biotech, pharma, frontier AI, or computational research environments is strongly preferred.

## 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
- [Applied ML Scientist (Staff / Principal)](https://feeny.ai/job/applied-ml-scientist-staff-principal-genesis-molecular-ai-san-mateo-ypytjf6pxab2) — 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
- [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