Associate Director and Senior Principal, AI Methods, AI for Research (AI4R)
Novartis
June 27, 2026
Remote friendly (Cambridge, MA)
United States
Clinical Research and Development
Key Responsibilities:
- Lead matrixed teams to design and deliver robust, scalable machine learning solutions for drug discovery
- Drive development of core ML capabilities across priority biomedical research AI use cases
- Identify methodological innovation opportunities across the end-to-end drug discovery pipeline
- Build advanced algorithms, models, and workflows to accelerate therapeutic discovery and development
- Establish and manage strategic collaborations with academic and external research partners
- Serve as subject matter expert on state-of-the-art ML approaches across research domains
- Translate model outputs into actionable scientific hypotheses and guide experimental design
- Define and implement success metrics for AI model impact
- Collaborate cross-functionally to align AI solutions with scientific and business objectives
- Promote adoption of advanced AI methods within the broader research organization
Essential Requirements:
- 6+ years developing and deploying ML solutions in drug discovery
- Hands-on ML experience in target identification, protein modeling, or translational research
- Experience with large-scale training, HPC, and cloud infrastructure
- Advanced knowledge of modern ML (e.g., representation learning, neural network architectures)
- Proficiency in Python and deep learning frameworks; strong software engineering and version control
- Proven ability to drive innovation in complex, matrixed environments
Desirable Requirements:
- Publications, patents, or open-source contributions in advanced ML
- Experience with multimodal/foundation models for biomedical data (imaging, genomics, molecular structures)
Compensation & Benefits (as stated):
- Salary: $160,300–$297,700 USD annually; plus performance-based cash incentive and, depending on level, annual equity awards; US comprehensive benefits (health, life, disability), 401(k) with match, and time-off.
- Lead matrixed teams to design and deliver robust, scalable machine learning solutions for drug discovery
- Drive development of core ML capabilities across priority biomedical research AI use cases
- Identify methodological innovation opportunities across the end-to-end drug discovery pipeline
- Build advanced algorithms, models, and workflows to accelerate therapeutic discovery and development
- Establish and manage strategic collaborations with academic and external research partners
- Serve as subject matter expert on state-of-the-art ML approaches across research domains
- Translate model outputs into actionable scientific hypotheses and guide experimental design
- Define and implement success metrics for AI model impact
- Collaborate cross-functionally to align AI solutions with scientific and business objectives
- Promote adoption of advanced AI methods within the broader research organization
Essential Requirements:
- 6+ years developing and deploying ML solutions in drug discovery
- Hands-on ML experience in target identification, protein modeling, or translational research
- Experience with large-scale training, HPC, and cloud infrastructure
- Advanced knowledge of modern ML (e.g., representation learning, neural network architectures)
- Proficiency in Python and deep learning frameworks; strong software engineering and version control
- Proven ability to drive innovation in complex, matrixed environments
Desirable Requirements:
- Publications, patents, or open-source contributions in advanced ML
- Experience with multimodal/foundation models for biomedical data (imaging, genomics, molecular structures)
Compensation & Benefits (as stated):
- Salary: $160,300–$297,700 USD annually; plus performance-based cash incentive and, depending on level, annual equity awards; US comprehensive benefits (health, life, disability), 401(k) with match, and time-off.