Director of AI Engineering

• Build AI that directly shapes R&D decisions
• Own foundational and predictive modeling end-to-end
• Advance generative AI for drug design
• Engineer elegant, reliable ML systems
• Decode high-dimensional biology
• Influence portfolio and strategy decisions
• Stay at the frontier
• Raise AI fluency across the organization
• Represent the science externally

• PhD or Master’s in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline
• 2–5 years of applied AI/ML experience
• Experience in life sciences preferred, but not required (pharma, biotech, or health tech)
• A working understanding of R&D workflows is preferred but not required, across target identification, lead optimization, translational science, clinical design, operations forecasting, or portfolio analytics
• Comfort operating across disciplines—chemistry, biology, pharmacology, statistics—with the ability to ground models in biological and clinical reality
• Demonstrated expertise in predictive modeling, generative AI, and ML system design
• Strong programming skills in Python and modern ML frameworks (e.g., PyTorch, TensorFlow), plus experience scaling models in cloud and/or HPC environments
• Proven ability to collaborate with other scientists, and could include laboratory bench researchers, clinicians, product teams, and business leaders
• Clear scientific communication, intellectual curiosity, and a mission-driven mindset focused on improving patient outcomes

• Experience in life sciences (pharma, biotech, or health tech)
• A working understanding of R&D workflows across target identification, lead optimization, translational science, clinical design, operations forecasting, or portfolio analytics

Relocation assistance may be available based on business needs and/or eligibility