Principal Machine Learning Engineer, BRAID

The Position

A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche.

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

Genentech is seeking a highly skilled and motivated Principal Machine Learning Engineer to join the Perturbation Biology group in Genentech Research and Early Development (gRED). Our dynamic and creative team is dedicated to developing the next generation of Machine Learning models to derive actionable insights from large-scale high-content perturbation experiments and to predict the outcome of unseen perturbations to drive experimental design. We are looking for an exceptional ML Engineer with demonstrated experience in developing, deploying, and supporting perturbation Foundation Models on massive internal datasets to guide target and drug discovery programs.

In this role, you will :

Maintain and advance Machine Learning algorithms to extract representations from multimodal high-content perturbation screens to identify promising novel drug targets, employing model classes such as vision transformers, causal representation learning and geometric deep learning.

Scale our Machine Learning techniques to massive datasets and lead the deployment of novel Machine Learning algorithms.

Develop and deploy frameworks for evaluating the performance of Foundation Models on large test datasets.

Collaborate with interdisciplinary and cross-functional teams including biologists, chemists, data scientists, and other stakeholders.

Contribute to software architecture and codebase quality, including documentation, testing frameworks, and version control.

Who you are

Educational Background : PhD degree in a quantitative field (?e.g., Computer Science, Physics, Engineering).

Experience :

Excellent knowledge of the practical application of advanced ML models in a research or industry setting.

Expertise with high-content perturbation datasets, and optimizing the training of machine learning models on these datasets.

Demonstrated interest in problems across biology and chemistry as applied to the discovery and development of treatments for disease.

Demonstrated ability to bridge research and engineering, turning prototype models into reliable, reusable tools for scientific users.

Contributions to open-source ML or scientific computing projects are highly valued.

Technical Skills :

Advanced skills in scientific programming in Python.

Extensive experience with Machine Learning frameworks and libraries (e.g., PyTorch, JAX, Tensorflow).

Proficiency in software engineering best practices : modular design, version control , testing, and continuous integration / deployment pipelines.

Soft Skills : Excellent communication, collaboration, and problem-solving skills.

Preferred

• Practical experience in scientific pipelining tools (e.g. airflow, snakemake, nextflow)

Relocation benefits are not available for this opportunity

The expected salary range for this position, based on the primary location of California, is $172,400 - 320,200. 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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