Senior Machine Learning Scientist

Roche • New York, NY

1d

About The Position

Roche’s Computational Sciences Center of Excellence brings together research and early development teams at Genentech and Pharma to use data and artificial intelligence to advance drug discovery and develop transformative medicines. Within Frontier Research, the role focuses on foundational machine learning research and new algorithmic frameworks for challenging biological questions. The team values open science, academic engagement, and contributions to the broader machine learning community, and operates with a flat scientific structure in which senior scientists shape their own research agendas with mentorship from leaders.

The Senior Machine Learning Scientist will develop and evaluate novel machine learning methods—particularly around causal representation learning and out-of-distribution generalization—and apply them to complex biological and drug-discovery problems. The position combines theoretical research, experimentation with deep-learning architectures, collaboration with global research teams, translation of biological challenges into computational models, and publication and presentation of findings. The primary posting location is Basel; the role may also involve collaboration across innovation hubs in Basel, New York, and San Francisco.

Requirements

• Currently pursuing a Ph.D. or holding an exceptional Master's degree in Computer Science, Statistics, Applied Mathematics, Computational Biology, Physics, or a closely related technical field, with strong practical research experience.
• Solid grounding in machine learning theory and principles, with practical familiarity or strong interest in causal representation learning and/or out-of-distribution generalization.
• Hands-on expertise building, training, and troubleshooting deep neural networks.
• Proficiency with modern deep learning frameworks; PyTorch is strongly preferred.
• Scientific contributions demonstrated through publications or accepted manuscripts at premier machine learning conferences or journals, such as NeurIPS, ICML, ICLR, AISTATS, UAI, CVPR, or ACL.
• Outstanding collaboration and interpersonal skills, including the ability to communicate complex technical ideas clearly across multidisciplinary, distributed global teams.
• Curiosity, unconventional problem-solving, and commitment to Roche’s values of Integrity, Courage, and Passion.

Nice To Haves

• Exposure to or strong interest in working with biological datasets and molecular systems; direct prior biological experience is an asset but not mandatory.

Responsibilities

• Design, implement, and benchmark novel machine learning algorithms grounded in causal representation learning and out-of-distribution generalization for complex biological problems.
• Frame foundational research questions beyond off-the-shelf machine learning paradigms and create robust, deployable architectures tailored to drug discovery.
• Collaborate with cross-functional research teams across the global innovation hubs in Basel, New York, and San Francisco.
• Build, experiment with, and scale unconventional neural network architectures using standard deep learning frameworks.
• Translate abstract biological challenges into rigorous computational models that connect machine learning theory with clinical impact.
• Author and drive scientific publications for submission to leading machine learning and computational biology venues.
• Present research findings and represent the Frontier Research team at internal symposia and international scientific conferences.
• Participate in knowledge-sharing, code reviews, and technical discussions to strengthen computational capabilities and support an open, innovative team dynamic.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior