Senior Machine Learning Scientist, (BRAID - Perturbation Biology)

Key Skills

Analytical and Problem solving, JAX framework, Machine learning techniques, NeurIPS, Python Programming, PyTorch, TensorFlow

Job Description

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.

Genentech seeks a highly skilled and motivated Senior Machine Learning Scientist to join the Perturbation Biology group within the BRAID (Biology Research | AI Development) department 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 committed to fostering innovation through cutting-edge ML methods with real-world impact in target and drug discovery.

The Opportunity

We are looking for exceptional researchers with a demonstrated research background in Machine Learning, a passion for interdisciplinary research and technical problem-solving, and a proven ability to develop and implement research ideas. The candidate is expected to routinely publish work in top-tier Machine Learning and scientific venues.

In this role, you will:

• Design and apply Machine Learning algorithms to guide and improve the experimental design of high-content perturbation screens for drug and target identification, employing model classes such as multimodal representation learning and geometric deep learning.

• Work on and integrate a variety of different data modalities such as molecular structures, omics data, images, and text.

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

• Build and scale Machine Learning techniques to massive datasets and aid in the deployment of novel Machine Learning algorithms.

• Publish in top-tier ML venues and/or scientific journals, present results at internal and external scientific venues, conferences, and workshops.

Who you are

• Educational Background: PhD degree in quantitative field (​e.g., Computer Science, Statistics, Mathematics) or in the physical or life sciences (e.g., Chemistry, Biology) with a strong quantitative focus.

• Experience:

• Proven track record of developing and applying advanced ML models in a research or industry setting.

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

• Technical Skills:

• Proficiency in scientific programming in Python.

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

• Strong background in statistics, probabilistic modeling and data analysis.

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

• Publications: Strong publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ICCV, etc.

Preferred

• Practical experience in one or more of the following areas:

• Predictive modeling of perturbation datasets with high-content readout (e.g., transcriptomics or image data)

• Modeling perturbation effects on heterogeneous cell states in transcriptomics data

• Predictive modeling and/or generative modeling on molecules and other chemistry applications

• Multimodal data integration, in particular between multiple measurement modalities and/or clinical patient data

Relocation benefits are available for this posting

The expected salary range for this position based on the primary location of California is $165,200 - 306,800. 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.