Senior Machine Learning Research Scientist, Structure and Simulation (AI for Drug Discovery)
Genentech Open · verified Oct 22, 2026 At a glance
Senior AI Research role at Genentech. New York · full-time · $160,900–$298,700 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and train large-scale foundation models for research questions in large-molecule discovery and protein engineering
- Use structural and biophysical data to create model designs that reflect molecular geometry and physical principles
- Work with researchers across the Computational Sciences Center of Excellence on shared research
- Publish your work, present findings internally and externally, and tackle drug discovery problems that support new portfolio capabilities
What you bring
- A related quantitative master’s degree plus five to ten years in industry, or a doctorate with more than two years of industry experience
- Practical Python and deep-learning library experience, with a record of designing and training models using modern methods
- Molecular dynamics and classical force-field expertise, plus hands-on work with molecular modeling software
- At least one first-author research paper or equivalent, and a public portfolio of computational projects
Who this fits
This senior research role suits someone focused on machine learning, structural biology and physical sciences, with experience applying models to drug discovery. The position is based in New York, and relocation benefits are unavailable.
From the employer
Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.
The Opportunity
At Roche's AI for Drug Discovery (AIDD) group (Prescient Design), We are building state-of-the-art foundation models and scalable systems to fundamentally transform how large and small molecule therapeutics are designed. We are looking for exceptional machine learning scientists who want to perform high-quality research at the intersection of machine learning, structural biology, and physical sciences to directly accelerate drug discovery.
In this role, you will:
● Design and train foundation models at scale to answer challenging research questions in large-molecule drug discovery and protein engineering.
● Leverage massive structural biology and biophysical datasets, building novel architectures that capture complex geometric and physical priors.
● Contribute to cross-functional research teams across the Computational Sciences Center of Excellence.
● Drive publications and present scientific findings at internal and external venues.
● Solve real, pressing problems in drug discovery that enable new portfolio capabilities
Who you are
● MS in Computer Science, Bioinformatics, Computational Biology, or a related quantitative field with 5-10 years of industry experience, or a PhD with +2 years of industry experience.
● Demonstrated experience with Python and deep learning libraries such as PyTorch and/or JAX.
● Demonstrated experience architecting and training deep learning models, particularly utilizing modern approaches (e.g., multimodal representation learning, geometric deep learning, and diffusion models).
● Expertise in molecular dynamics simulations and classical force fields (e.g., AMBER, CHARMM, OpenFF), as well as hands-on experience with molecular modeling tools (e.g., OpenMM, Rosetta).
● Demonstrated research experience, including at least one first author publication (or equivalent).
● Strong communication and collaboration skills
● Public portfolio of computational projects (available on e.g. GitHub)
Relocation benefits are NOT available for this job posting
The expected salary range for this position, based on the primary location of New York, is $160,900 - 298,700. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
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