Director, Generative AI

Role Summary

Director, Generative AI at the ShinrAI Center for AI/ML, based in Cambridge, MA. We seek individuals with deep knowledge of machine learning and artificial intelligence, especially Generative AI, to advance AI in developing innovative medicine for patients. The role involves solving real-world problems, collaborating across teams, and contributing to a diverse, high-impact environment.

Responsibilities

• Partner with data science teams, domain experts, and business units to identify and prioritize opportunities to leverage machine learning, generative AI, and agentic AI to drive decision making and automation across R&D.
• Translate business needs into clearly scoped machine learning projects and lead solution design and implementation.
• Educate and enable the application of machine learning and generative AI in pharmaceutical R&D operations and scientific domains.
• Identify, monitor, and validate external AI/ML developments; cultivate relationships with external experts and partners; report and present developments to shape long-term strategy and governance.
• Build cross-functional relationships to inform work and contribute to collaborations, including writing insightful, actionable pieces for internal decision makers.
• Be a leading voice for building capability and adopting best practices.
• Work with Ethics and Governance teams to ensure ethical AI/ML applications with broad patient and business benefits.
• Help AI/ML engineers and data scientists grow professionally.
• Measure, document, and communicate impacts of the Center’s efforts.

Qualifications

• Track record of partnering cross-functionally to develop and deploy novel data solutions in production environments.
• Ability to communicate complex technical topics simply to a wide range of audiences.
• Experience translating big-picture ideas into micro use cases with a focus on solving core problems.
• Experience recognizing and communicating implications of emerging technologies.
• Excellent communication, prioritization, and interpersonal skills with strong attention to detail.
• Advanced degree (M.S., PhD) in mathematics, applied statistics, computer science, machine learning, or similar; 8+ years of experience architecting, building, launching, and maintaining end-to-end ML systems at scale across multiple models and platforms; experience building agentic and LLM-based solutions; fine-tuning large language models for domain-specific applications; designing transfer learning strategies for small datasets; deep knowledge of AI/ML problems across domains (e.g., computer vision, NLP, RL, multimodal learning, etc.); strong understanding of deep learning architectures and ML/Ops concepts; experience delivering custom software solutions for complex R&D needs; proficiency with DevOps practices and standard software engineering workflows.
• Enthusiasm to ask questions and learn; entrepreneurial experience is desirable.
• Experience in life sciences/healthcare and experience in a complex global organization is a plus.

Skills

• Cross-functional collaboration
• Effective communication of complex concepts
• Problem solving and product-minded thinking
• Awareness of emerging AI technologies
• Software development and DevOps practices
• ML modeling, evaluation, and deployment

Education

• Advanced degree (M.S., PhD) in relevant fields as listed above.