Applied ML Scientist, Cheminformatics ( Staff / Principal)

Genesis Therapeutics; New York (NY); On-site; USD 90,000 - 160,000; Full time

Job summary

Join a forward-thinking company at the forefront of AI innovation in biochemistry. This unique role bridges AI research and experimental drug discovery, where you will leverage cutting-edge techniques to enhance drug discovery programs. Collaborate with talented professionals to evaluate and analyze models that drive impactful discoveries. If you have a strong background in data science, cheminformatics, and machine learning, this is an exciting opportunity to contribute to groundbreaking therapies for patients with severe disorders. Be part of a team that values creativity, collaboration, and a commitment to improving lives through innovative science.

Benefits

Competitive compensation package

Comprehensive health benefits

401(k) plan

Open PTO policy

Free lunches and dinners

Paid family leave

Life and disability insurance

Qualifications

• Experience in drug discovery and modeling small molecule datasets.
• Strong data science and software engineering skills are essential.

Responsibilities

• Collaborate with AI and drug discovery teams to evaluate model performance.
• Assist in interpreting model predictions and curate datasets.

Skills

Data Science

Machine Learning

Chemoinformatics

Software Engineering

Experimental Techniques

Statistical Methods

Exploratory Data Analysis

Deep Neural Networks

Education

PhD in Cheminformatics

Bachelor's in Computer Science

Tools

Python

Numpy

Matplotlib

RDKit

OpenEye

PyTorch

Scikit-learn

SQL

Job description

About the Team

We’re a tight-knit team of proven drug hunters, deep learning researchers, and software engineers united by a common mission — drive AI innovation in biochemistry, discovering and developing groundbreaking therapies for patients suffering from severe disorders.

The Genesis AI team is focused on developing foundation models for drug discovery by conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, as well as engineering robust software systems that enable running large scale simulations and training generative and predictive AI models designed to learn from all kinds of molecular data, leveraging our cluster with 1000s of GPUs and 10,000s of CPUs.

About the Role

This unique role serves as a critical bridge between our AI research and experimental drug discovery teams. You will collaborate closely with both groups, leveraging cutting-edge AI techniques to evaluate, analyze, and deploy models to maximize the impact of our industry-leading AI platform on drug discovery programs.

The ideal candidate will be comfortable in experimental and engineering contexts and skilled at communicating with stakeholders from both domains. Their day-to-day responsibilities will require basic familiarity with experimental techniques, excellent data science skills, and demonstrated ability in applied ML.

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

You will

• 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

• Experience working with chemistry project teams in an industrial or academic drug discovery setting.
• Experience with modeling and analysis of small molecule datasets.
• Familiarity with common experiment types (biochemical/binding/cell-based assays, in vivo studies, etc.) and CADD workflows (docking, virtual screening, ADME prediction, etc.).
• Excellent data science skills, including exploratory data analysis and statistical methods for model comparison and evaluation.
• Strong software engineering skills, including experience with Python, Numpy, and Matplotlib.
• Strong cheminformatics skills, including experience with RDKit or OpenEye.
• Strong applied ML background, including familiarity with deep neural networks and experience with scikit-learn and PyTorch.

Nice to have's

• Publications in peer-reviewed journals or conferences describing ML applications in drug discovery or related areas.
• PhD or equivalent in cheminformatics, computer-aided drug design, or a related field.
• Experience with graph neural networks, multitask modeling, active learning, Bayesian optimization, model uncertainty, and multi-objective optimization.
• Experience with implementation of ML model architectures in PyTorch.
• Experience in a collaborative software engineering environment, including code reviews and pull request workflows.
• Experience with SQL and database management.
• 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 Therapeutics

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 signed AI-focused platform collaborations with major pharmaceutical companies, including most recently Incyte Corporation (Feb 2025) and Gilead Sciences (Sept 2024).

We raised a $200M series B in August 2023, and have raised over $300M 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.