Senior Scientist - Agentic AI Systems

Sanofi•Toronto, ON

3d•CA$127,000 - CA$177,000•Onsite

About The Position

Join Sanofi’s Digital R&D as a Senior Scientist, where you will design, develop, and deploy cutting-edge autonomous AI agents to transform drug discovery, clinical research, and biomedical data analysis. In this role, you will work at the forefront of artificial intelligence and life sciences, translating complex scientific and clinical challenges into scalable agentic AI solutions. You will collaborate closely with AI engineers, data scientists, and R&D stakeholders to build intelligent systems that reason, plan, and act autonomously accelerating scientific discovery and improving patient outcomes. This position offers a unique opportunity to contribute deep technical innovation in agentic AI while working on high-impact pharmaceutical applications that support Sanofi’s mission to chase the miracles of science.

Requirements

Ph.D. or M.S. in Computer Science, Artificial Intelligence, Machine Learning, Biomedical Engineering, Computational Biology, or related field
1+ years of experience building AI/ML models and systems in research or production environments
Deep expertise in large language models, transformers, and modern deep learning architectures
Strong Python programming skills and experience with ML frameworks (PyTorch, TensorFlow, JAX)
Hands-on experience with agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI, or similar)
Experience designing agentic components such as memory systems, planning engines, reasoning modules, and tool-calling pipelines
Familiarity with distributed systems, cloud platforms (AWS, Azure, GCP), and MLOps tools (MLflow, W&B, CI/CD)
Strong analytical and problem-solving skills, especially in complex scientific or healthcare data contexts
Excellent communication skills and ability to explain technical concepts to multidisciplinary stakeholders

Nice To Haves

Proven track record of publications in top-tier AI/ML or healthcare informatics conferences
Experience applying AI to drug discovery, genomics, imaging, clinical trials, or real-world evidence
Experience with vector databases, retrieval-augmented generation (RAG), and knowledge graphs
Familiarity with regulatory and compliance considerations in healthcare AI
Experience working in cross-functional, global R&D organizations
Active GitHub profile with open-source contributions, reproducible research code, or production-grade AI/ML systems

Responsibilities

Design and implement state-of-the-art agentic AI systems for drug discovery, clinical development, and R&D operations
Develop multi-agent architectures incorporating perception, memory, planning, reasoning, and tool-use modules
Build and evaluate autonomous AI workflows for scientific data analysis, hypothesis generation, and decision support
Translate real-world biomedical and clinical research problems into AI-driven solutions in partnership with R&D scientists
Conduct research on novel agentic AI algorithms, architectures, and evaluation frameworks
Implement scalable, production-ready AI pipelines with robust monitoring, logging, and governance
Ensure AI systems comply with regulatory, quality, and responsible AI principles in pharmaceutical environments
Contribute to scientific publications, patents, and internal technical knowledge sharing
Collaborate with cross-functional teams including digital product owners, clinical scientists, and platform engineers
Mentor junior scientists and contribute to a culture of scientific excellence and continuous learning