Machine Learning Scientist

Roche
Roche logo
Location
Basel, Basel-City
Job Type
Full-time
Posted
October 6, 2026
Views
2

Job Description

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

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.


The Opportunity


  • 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

Who You Are


  • 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 PyTorch
  • 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

Preferred Qualifications


  • 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)

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

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.


The Opportunity


  • 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

Who You Are


  • 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 PyTorch
  • 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

Preferred Qualifications


  • 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)

About AI Biology & Translation (AIBT)


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.

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.


Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.

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Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The job is located in Basel, Basel-City. The job posting does not specify a remote, hybrid, or on-site work-mode policy.
What are the key responsibilities of this role?
You will build, train, and fine-tune machine learning algorithms to optimize nucleic acid-based medicines. You will design candidate sequence libraries, analyze experimental readouts, collaborate cross-functionally with wet-lab scientists, present technical findings, stay current with biological sequence modeling advancements, and contribute to scientific publications.
What required qualifications and experience do I need?
You need a Ph.D. in a quantitative discipline (such as Bioinformatics, Computational Biology, Computer Science, or Machine Learning) with 0-4 years of post-doctoral or industry experience. You must have strong Python and PyTorch skills, hands-on experience with sequence-to-function models, research impact in ML and molecular biology, and excellent English communication skills.

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Research the company before you apply.

  • 13 open roles
  • Verified H-1B salary data
  • Clinical-trial hiring momentum
  • Culture, benefits & locations
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Job Information

Source: manual
AI Relevance: 85/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
roche machine learning deep learning artificial intelligence bioinformatics computational biology genomics oncology

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