Genesis is building a world-class ML team in an industry that has underutilized computational methods for too long. We are creating the best molecular generation and property prediction platform in the world, filling in a critical piece in the drug discovery process. We need you to drive the cutting-edge research that will enable us to find cures for a wider range of diseases, faster than ever before.

You will

Drive speed and accuracy improvements in our ML platform, coming up with architecture modifications for 2D and 3D graph neural networks, and rapidly implementing and testing them in pytorch
Keep up with deep learning research, especially pertaining to graph neural nets and graph generative models, and quickly prototype ideas gleaned from the literature
Dive deep into molecular datasets, creating statistically rigorous train, valid, and test sets to optimally train our models for real-world prediction and generation tasks
Develop creative featurizations of 2D and 3D molecular structures that are inspired by laws of physics and chemistry, enabling our networks to take better advantage of available data
Work closely with software engineers and medicinal chemists to make our ML platform maximally adaptive to different use cases

You are

A strong software engineer who will write code quickly and uphold our code quality standards
Comfortable with linear algebra and statistics
Experienced applying traditional ML techniques and/or deep learning to real-world problems
A deep thinker who reasons from first principles over pattern matching
Interested in learning about machine learning, biochemistry, and the drug development process

What We Offer

The opportunity to work on challenging, high impact ML research that is 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 ML 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

Genesis Therapeutics is unifying AI and biotech to discover novel and breakthrough treatments for patients with severe and devastating conditions. Genesis was founded on groundbreaking molecular ML research and since has established itself as the industry leader in AI for small molecule drug discovery. Our team of accomplished biotech leaders and expert drug hunters joins forces with deep learning researchers and software engineers who are pioneering predictive and generative AI technologies for molecules.

Our team has created the industry's most advanced molecular AI platform called GEMS (Genesis Exploration of Molecular Space), to accelerate and optimize small molecule drug discovery and to enable the discovery of novel first-in-class and best-in-class small molecule drugs for challenging and/or undruggable targets.

The company has leveraged GEMS to build an internal pipeline with multiple programs against high-value targets, including data-poor and canonically undruggable targets where GEMS is uniquely advantaged. In addition, Genesis has two AI platform collaborations across a range of therapeutic areas: Eli Lilly (signed in 2022, with a $20M upfront payment and a $670M total deal size), and Genentech (signed in 2020).

We raised a $200M series B in August 2023, and have raised over $280M in funding from top technology and biotech investors, including Andreessen Horowitz, Rock Springs Capital, T. Rowe Price, Fidelity, Radical Ventures, NVentures (NVIDIA's VC arm), BlackRock, and Menlo Ventures.

Genesis is headquartered in Burlingame, CA, with a fully integrated laboratory in San Diego. We are proud to be an inclusive workplace and an Equal Opportunity Employer.

Finding the best talent is our top priority at Genesis Therapeutics. If you are interested in potential partnership on recruitment, please reach out to recruiting@genesistherapeutics.ai.

Genesis Therapeutics

New Jobs

ML Research Engineer (New Grad)