Director and Group Head, Applied AI
Novartis
August 12, 2026
On-site
Cambridge, MA
IT
About The Role
Director & Group Head (Applied AI): Lead applied machine learning efforts to accelerate drug discovery, translating complex data into scientific insights and improving patient outcomes. Lead collaborations, set strategic AI direction across research domains, and enable teams to develop better medicines faster.
Key Responsibilities
- Define and lead the applied AI strategy and multi-year roadmap across drug discovery research.
- Align priorities with portfolio needs, scientific opportunities, and measurable business/research impact.
- Lead multidisciplinary teams to identify, prototype, benchmark, and deploy fit-for-purpose AI solutions.
- Govern an applied AI portfolio: intake, prioritization, resourcing, delivery oversight, and success metrics.
- Establish best practices for problem framing, data readiness, benchmarking, evaluation design, and reproducible model development.
- Drive benchmarking of foundation and task-specific models to enable informed adoption decisions.
- Partner with engineering teams to scale solutions and embed them into day-to-day scientific decision making.
- Define evaluation metrics linking model performance to downstream decisions and experimental outcomes.
- Build a culture of scientific rigor, rapid iteration, mentorship, and practical impact.
- Forge academic and industry collaborations to accelerate innovation, benchmarking, and technology transfer.
Essential Requirements
- Demonstrated experience leading core ML capability development across drug discovery teams/use cases.
- Proven experience benchmarking foundation models in drug discovery applications.
- Hands-on ML experience in drug discovery (e.g., target identification, computational chemistry).
- Experience with large-scale training, distributed computation, model adaptation, and deployment in MLOps.
- Passion for biomedical sciences/therapeutic discovery; ability to explain complex technical concepts.
- 12+ years in innovation, development, deployment, and continuous support of ML/modeling solutions.
- Strong Python and deep learning framework proficiency; experience with Git/version control.
- Ability to manage complexity and drive outcomes in matrixed environments.
Desirable Requirements
- Publications, patents, or open-source contributions demonstrating ML innovation and domain expertise.
- Pragmatic ability to apply emerging technologies to real-world business challenges.
Compensation & Benefits
- Salary expected to range from $194,600–$361,400 annually; performance-based cash incentive; potential annual equity awards; US-based comprehensive benefits and time-off.
Application Instructions
- None provided.
Director & Group Head (Applied AI): Lead applied machine learning efforts to accelerate drug discovery, translating complex data into scientific insights and improving patient outcomes. Lead collaborations, set strategic AI direction across research domains, and enable teams to develop better medicines faster.
Key Responsibilities
- Define and lead the applied AI strategy and multi-year roadmap across drug discovery research.
- Align priorities with portfolio needs, scientific opportunities, and measurable business/research impact.
- Lead multidisciplinary teams to identify, prototype, benchmark, and deploy fit-for-purpose AI solutions.
- Govern an applied AI portfolio: intake, prioritization, resourcing, delivery oversight, and success metrics.
- Establish best practices for problem framing, data readiness, benchmarking, evaluation design, and reproducible model development.
- Drive benchmarking of foundation and task-specific models to enable informed adoption decisions.
- Partner with engineering teams to scale solutions and embed them into day-to-day scientific decision making.
- Define evaluation metrics linking model performance to downstream decisions and experimental outcomes.
- Build a culture of scientific rigor, rapid iteration, mentorship, and practical impact.
- Forge academic and industry collaborations to accelerate innovation, benchmarking, and technology transfer.
Essential Requirements
- Demonstrated experience leading core ML capability development across drug discovery teams/use cases.
- Proven experience benchmarking foundation models in drug discovery applications.
- Hands-on ML experience in drug discovery (e.g., target identification, computational chemistry).
- Experience with large-scale training, distributed computation, model adaptation, and deployment in MLOps.
- Passion for biomedical sciences/therapeutic discovery; ability to explain complex technical concepts.
- 12+ years in innovation, development, deployment, and continuous support of ML/modeling solutions.
- Strong Python and deep learning framework proficiency; experience with Git/version control.
- Ability to manage complexity and drive outcomes in matrixed environments.
Desirable Requirements
- Publications, patents, or open-source contributions demonstrating ML innovation and domain expertise.
- Pragmatic ability to apply emerging technologies to real-world business challenges.
Compensation & Benefits
- Salary expected to range from $194,600–$361,400 annually; performance-based cash incentive; potential annual equity awards; US-based comprehensive benefits and time-off.
Application Instructions
- None provided.