Director, World Model & Agentic Learning

Role

Lead the AI science team focused on developing J&J's enterprise world model and agentic-learning capabilities within the Generative AI organization. Primary objectives include designing systems for knowledge accumulation, reasoning, self-assessment, and continuous improvement from real-world operation and expert feedback.

Responsibilities

• setting technical direction
• building mechanisms for knowledge representation, confidence estimation, and reasoning
• partnering with scientists and domain experts to embed expert judgment into AI systems
• leading a team of 4-8 AI scientists
• establishing a culture of rigor and accountability
• collaborating across R&D, data, and AI evaluation functions

Qualifications

• minimum 8 years in industry AI/ML system development, with hands-on experience in large language models, knowledge representation, and systems emphasizing continual learning and knowledge accumulation

Preferred

• advanced degree (PhD)
• experience in regulated environments such as life sciences or healthcare
• expertise in knowledge graphs or explicit knowledge systems

High Value

• focus on knowledge-based reasoning, continual learning, agentic AI, and application within life sciences or healthcare R&D

Work setup

hybrid locations in the US, including Cambridge, MA; La Jolla, CA; Titusville, NJ; or Spring House, PA.