Principal Machine Learning Scientist for Protein Design

_About the job_ The opportunity: Join Sanofi's Biologics AI & Design team at the forefront of a revolution in drug discovery. We're building next-generation foundational models that are directly shaping our therapeutic pipeline — designing antibody and NANOBODY® molecules that will become tomorrow's medicines for patients worldwide. What makes this role unique:
- Proprietary biological data at scale — Access to one of the world's largest proprietary datasets of antibody sequences, structures, and functional annotations from decades of therapeutic development
- World-class compute infrastructure — State-of-the-art GPU clusters and cloud resources for training large-scale foundational models
- Real therapeutic impact — Your models will be validated against real targets and integrated into live drug discovery programs
- Scientific freedom — We encourage publication, conference participation, and collaboration with leading academic labs
- Global collaboration — Work with interdisciplinary teams across computational biology, protein engineering, and therapeutic development

What You'll Do
Build the future of protein therapeutics design:
- Architect and train next-generation foundational models for antibody and NANOBODY® design, including protein language models, structure prediction models, diffusion-based generative models, and multimodal architectures
- Push the boundaries of generative protein design — develop novel training strategies, fine-tuning approaches, and inference methods that leverage Sanofi's unique biological data assets
- Validate rigorously — design benchmarking strategies and work with wet-lab teams to experimentally validate model predictions on therapeutically relevant targets
- Collaborate across disciplines — partner with antibody engineers, structural biologists, screening teams, and therapeutic area experts to understand biological constraints and opportunities
- Stay at the cutting edge — monitor emerging architectures and methods, evaluate their potential, and rapidly prototype new approaches
- Contribute to the scientific community — publish your work, present at conferences, and help establish Sanofi as a leader in AI-driven biologics design **_ About you_*
* What You Bring Education & Experience:
- Ph.
D. in computational life sciences, computer science, machine learning, bioinformatics, or related field (or M.
Sc. with exceptional track record)
- Deep expertise in modern deep learning architectures
- transformers, diffusion models, flow matching, VAEs, or other generative modeling paradigms
- Hands-on experience training large-scale models
- you've trained models with millions to billions of parameters and understand distributed training, optimization strategies, and scaling laws
- Strong foundation in protein science
- understanding of protein sequence-structure-function relationships, ideally with focus on antibodies or therapeutic proteins
- Publication track record demonstrating impact in foundational model development, generative modeling, and/or computational protein design
- undefined Technical Excellence
- Expert-level Python programming and deep learning frameworks
- Proficiency with distributed training frameworks and cloud/HPC environments
- Software engineering practices
- version control, testing, documentation, reproducibility
- Familiarity with biological databases, sequence analysis tools, and structural biology software Personal Attributes:
- Intellectual curiosity
- you're excited by hard scientific problems and driven to solve them
- Collaborative mindset
- you thrive in interdisciplinary environments and can communicate complex technical concepts to diverse audiences
- Scientific rigor
- you design robust experiments, think critically about limitations, and are honest about uncertainty
- Self-motivated
- you can work independently, prioritize effectively, and drive projects forward
- Passion for impact
- you're motivated by the opportunity to develop medicines that improve patients' lives _

About us
_

What We Offer
Scientific Environment:
- Access to proprietary biological datasets unavailable anywhere else
- State-of-the-art computational infrastructure (GPU clusters, cloud resources)
- Freedom to publish and present at top-tier conferences
- Collaboration with leading academic partners and external research groups
- Opportunity to shape the future of AI-driven drug discovery Professional Growth
- Work alongside world-class experts in protein engineering, structural biology, and machine learning
- Exposure to the full drug discovery lifecycle
- from target selection to pre-clinical development
- Mentorship opportunities and career development support
- Access to internal training, conferences, and scientific networks Impact & Mission:
- Your work will directly contribute to therapeutic programs addressing serious dis