Senior Machine Learning Scientist, Frontier Research, AI for Drug Discovery

About Roche and Genentech

Genentech, a member of the Roche group and founder of the biotechnology industry, is dedicated to pursuing groundbreaking science to discover and develop medicines for people with serious and life-threatening diseases. Roche's mission is to create a healthier future by advancing science and ensuring everyone has access to the healthcare they need today and for generations to come.

About the Computational Sciences Center of Excellence

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.

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 scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

The Opportunity

Frontier Research is dedicated to foundational machine learning research and the development of new algorithmic frameworks. The organization operates with a flat scientific structure in which senior scientists define their own research agendas, and leaders act as mentors who shape priorities across the organization.

Open science is a core value and competitive necessity. The commitment to open dissemination, academic engagement, and community contribution ensures that work contributes meaningfully to the broader machine learning community and advances the scientific ecosystem.

In biology, many exciting research questions cannot yet be addressed with off-the-shelf ML approaches—they demand not only novel solutions but also new ways of framing the questions themselves, often beyond existing ML paradigms. Self-supervised representation learning and generative modeling provide the most promising paths to connect these fields and build robust, impactful solutions.

Your Responsibilities

• Develop methods in self-supervised representation learning and generative modeling
• Contribute to publications and present results at internal and external scientific conferences
• Collaborate and execute on research that pushes forward the state of the art in machine learning
• Directly contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results
• Work with a large and globally distributed team

Requirements

• PhD degree in Mathematics, Physics, Computer Science, Statistics, Machine Learning, or related disciplines
• 0–2+ years of industry or post-doc experience with a focus on deep learning
• Publications in academic journals like JMLR or at peer-reviewed ML conferences (e.g., NeurIPS, CVPR, ICML, ICLR, COLT, ICCV, AISTATS, ACL)
• Strong communication and collaboration skills

Preferred Qualifications

• Published work with theoretical contributions
• Experience with research related to representation learning and generative modeling
• Public portfolio of computational projects (available on e.g., GitHub)

Compensation and Benefits

Expected Salary Range:

• San Francisco: $168,100 - $312,300
• New York City: $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 additional benefits.

Note: Relocation benefits are NOT available for this job posting.

Equal Opportunity

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. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing the Accommodations for Applicants form.