Software Engineer - Core Infrastructure at Genesis Molecular AI (San Mateo, CA)

Genesis Molecular AI· San Mateo, CA·3d ago

Role details

Employment

Full-Time

Job description

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

You Will

Work on our infrastructure team to maintain and grow our multi-cloud compute infrastructure that supports our ML model training, computational chemistry research, and ongoing drug discovery efforts
Build out our configuration and procedures for monitoring, resource allocation, and deployment automation, as we continue to grow our autoscaling compute clusters to handle larger workloads
Work on orchestration scheduling framework to increase our execution throughput, reliability, and compute utilization across heterogeneous pipelines

You Are

5+ years of experience building and maintaining cloud infrastructure at scale, e.g. within AWS or GCP
Proficient with Python, Bash, Terraform, Ray and Kubernetes
Ideally, experience building and maintaining compute clusters running distributed ML training jobs with 1,000+ GPUs
Nice to have: hands-on experience with physical hardware + datacenter management

What We Offer

The opportunity to work on high impact infrastructure that is used to accelerate the discovery of new medicines
A world-class, tight-knit team of good-hearted people across software, machine learning, computational chemistry, medicinal chemistry, and biology
Competitive salary and equity. Medical, dental, and vision insurance, and a 401(k) program

About Genesis Molecular AI

Genesis Molecular AI 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 businesswire.com 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 forbes.com and GEN genengnews.com) 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.

Why work at Genesis Molecular AI

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.

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: 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: 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.

Sources

Job description

What We Offer

About Genesis Molecular AI

Why work at Genesis Molecular AI

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