Senior Machine Learning Scientist, Protein ML, AI for Drug Discovery (AIDD)

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 this 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 within the Computational Sciences Center of Excellence, we are driving a paradigm shift in how large molecule drug discovery is conducted. Our vision is to integrate artificial intelligence and machine learning into every stage of antibody discovery—from target assessment and design optimization to developability prediction and portfolio prioritization.

We are seeking a highly motivated Senior Machine Learning Scientist to join the AIDD group within Genentech Research and Early Development (gRED) to help drive our research on Machine Learning for Drug Discovery. The successful candidate will collaborate extensively with computational and experimental scientists and researchers across gRED to design and apply next-generation ML models to biology and large molecule drug discovery.

What you'll do:

• Develop generative and representation learning machine learning models for protein and antibodies in zero-shot and few-shot regimes.
• Closely collaborate with scientists and researchers across disciplines and teams to build impactful technologies for drug discovery research.
• Build and scale machine learning techniques to massive datasets.
• Contribute to and drive publications, present results at internal and external scientific conferences.
• Who you are
• BS, MS, or PhD  degree in the physical sciences (e.g. Chemistry, Physics, Chemical Engineering) or quantitative field (​e.g.​ Computer Science, Statistics, Applied Mathematics) or equivalent industry research experience (3+ years for BS or MS).
• Extensive experience working with large datasets, including graph, sequence, and 3D point clouds.
• Record of scientific excellence as evidenced by at least one first author publication in a scientific journal or machine learning conference.
• Public portfolio of projects available on GitHub
• Excellent communication and interpersonal skills.
• Highly-motivated and independent self starter that is eager to collaborate.
• Demonstrated experience with modern Python frameworks for deep learning like PyTorch.
• Preferred
• Record of machine learning research excellence as evidenced by publications in computer science and machine learning conferences (e.g. NeurIPS, ICLR, ICML).
• Experience in developing ML models for images, 3D point clouds, video generation.Anchor Role:
• Relocation benefits are NOT available for this job posting

The expected salary range for this position, based on the primary location of California, is $167,400 - 310,800. 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.