Machine Learning Scientist

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The Position AI Biology & Translation (AIBT) develops and applies state-of-the-art artificial intelligence to accelerate biomedical discovery across Research and Early Development in Genentech & Roche. We combine advances in foundation models, multimodal machine learning, and large-scale biological data to advance target discovery, disease understanding, biomarker development, and translational science. We are seeking a (Senior) ML Scientist with deep expertise in modern machine learning to lead the development and application of next-generation AI technologies for designing DNA and RNA sequences for nucleic acid-based medicines.

We work closely with stakeholders in Cell Therapy, Gene Therapy, and Vaccine Oncology on diverse projects, ranging from platform development for lab-in-the-loop refinement of sequence designs to lead optimization for portfolio projects. Representative work includes designing regulatory elements to confer cell-type-specific transcription and engineering synonymous coding sequences to enhance translational efficiency. As a Scientist / Senior Scientist, you will directly lead sequence design campaigns, translating biological questions into predictive and generative models, and driving iterative sequence optimization in close collaboration with wet-lab experimentalists.

• Build, train, and fine-tune machine learning algorithms to optimize nucleic acid-based medicines for active portfolio projects
• Design candidate sequence libraries for lab-in-the-loop optimization cycles, analyze experimental readouts (e.g., MPRA, NGS), and iteratively update designs
• Collaborate cross-functionally with wet-lab scientists and project leads to understand therapeutic constraints and tailor design algorithms accordingly
• Present technical findings, candidate designs, and model performance metrics to cross-functional team members and stakeholders
• Stay current with advancements in biological sequence modeling and nucleic acid therapeutics to bring state-of-the-art methods into our pipeline
• Contribute to scientific publications

• Ph.D. in a quantitative discipline (Bioinformatics, Computational Biology, Computer Science, Machine learning, or a related field) with 0-4 years of post-doctoral or industry experience
• Demonstrated research impact at the interface of machine learning and molecular biology, evidenced by publications in top-tier journals or ML conferences
• Strong Python programming skills and proficiency in deep learning frameworks such as Py Torch
• Hands-on experience developing, training, or fine-tuning sequence-to-function models for biological molecules (preferably DNA/RNA)
• Excellent communication skills in English, with the ability to speak to both computational and experimental scientists

• Prior experience applying machine learning in a biotech, pharma, or industry setting
• Domain knowledge in nucleic acid-based therapeutics (e.g., mRNA design, AAV capsid/promoter engineering, cell therapy vectors)
• Experience with advanced ML frameworks relevant to sequence design, such as generative modeling (diffusion, autoregressive sequence models, masked language models), active learning, model interpretability, or uncertainty quantification
• Familiarity with high-throughput functional genomics data processing (e.g., MPRA, RNA-seq, ribosome profiling)

AI Biology & Translation (AIBT) is part of the Computational Sciences Center of Excellence (CS-CoE). AIBT advances the development and application of cutting-edge artificial intelligence to accelerate biomedical discovery and translational science. By integrating expertise in machine learning, computational biology, and software engineering, AIBT develops AI capabilities that enable researchers to generate new biological insights, accelerate scientific decision-making, and transform research across Genentech & Roche.

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