Director, World Model & Agentic Learning

Scorpion Therapeutics; Cambridge (MA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Johnson & Johnson's Generative AI organization in the U.S. seeks a leader to head the AI science team focused on enterprise world models and agentic learning for R&D applications.

You will design systems for knowledge accumulation, reasoning, and continual improvement over real-world scientific data, partnering with domain experts and evaluation teams to ensure high-quality AI decisions.

Qualifications

• 8+ years in AI/ML with hands-on knowledge of knowledge representation, continual learning and reasoning systems.
• Proven leadership in building and guiding scientific or technical teams.
• Strong communication for cross-disciplinary stakeholder alignment.

Responsibilities

• Architect mechanisms for structured knowledge representation, confidence estimation, and self-improvement.
• Partner with domain experts to integrate scientific expertise.
• Oversee team recruitment and development.
• Ensure system accountability, traceability, and auditability.
• Collaborate with evaluation and platform teams to validate decision quality.

Skills

AI/ML leadership

Team leadership

Cross-disciplinary communication

Job description

Role

Lead the AI science team within Johnson & Johnson's Generative AI organization, focusing on developing enterprise world models and agentic learning capabilities for R&D applications.

Objectives

Design and implement systems that enable knowledge accumulation, reasoning, self-assessment, and continual improvement over real-world scientific data.

Responsibilities

• Architect mechanisms for structured knowledge representation, confidence estimation, and self-improvement;
• Partner with domain experts to integrate scientific expertise;
• Oversee team recruitment and development;
• Ensure system accountability, traceability, and auditability;
• Collaborate with evaluation and platform teams to validate decision quality.

Qualifications

• 8+ years in AI/ML, with extensive hands-on experience designing knowledge representation, continual learning, and reasoning systems;
• Proven leadership in building and guiding scientific or technical teams;
• Strong communication skills for cross-disciplinary stakeholder alignment.

High-Value

• Focus on knowledge accumulation, agentic frameworks, structured memory, and continual learning in regulated or high-stakes environments such as life sciences or healthcare R&D;
• Experience with AI system architecture, active learning, and domain-specific knowledge integration preferred.

Work setup

Hybrid in U.S. offices (Titusville, NJ; Spring House, PA; Cambridge, MA; La Jolla, CA); travel expectations not specified.