Senior Machine Learning Research Scientist, Structure and Simulation (AI for Drug Discovery)

Genentech; New York (NY); On-site; USD 161,000 - 299,000; Full time

Job summary

Genentech is seeking exceptional machine learning scientists for the AI for Drug Discovery group. We design state-of-the-art foundation models and scalable systems to transform how large and small molecule therapeutics are designed, leveraging structural biology data to accelerate drug discovery.

You will contribute to cross-functional teams, drive publications, and present findings at internal and external venues.

Qualifications

• 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)

Responsibilities

• 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

Skills

Python

Deep learning

Multimodal learning

Geometric deep learning

Molecular dynamics

Education

MS/PhD in CS/Bioinformatics/Computational Biology

Tools

OpenMM

Rosetta

AMBER

CHARMM

OpenFF

Job description

The Position

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.

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.

Benefits

#ComputationCoE

#tech4lifeComputationalScience

#tech4lifeAI

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

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