Principal Scientist - AI/ML Workflow & Ecosystem Lead

Job Summary Lets do this. Lets change the world. In this vital and exciting role, you will serve as a Principal Scientist within the Research organization, leading the integration and scaling of artificial intelligence and machine learning (AI/ML) capabilities across the Large Molecule Discovery (LMD) informatics ecosystem. You will be responsible for translating advanced computational models into robust, production-ready solutions that are embedded within scientific workflows and drive measurable impact across biologics research.

As a scientifically grounded leader, you will work closely with experimental and computational scientists to understand research needs and translate them into clear data, workflow, and platform requirements, partnering with technology teams to deliver scalable, production-grade solutions. You will operate at the intersection of science, data, and technology, ensuring that AI/ML capabilities are effectively deployed, adopted, and sustained within a complex RD environment.

This role plays a key role in advancing AI/ML implementation within Large Molecule Discovery (LMD), working collaboratively with enterprise partners to align with and contribute to broader AI/ML strategies.

This role leads a horizontally integrated AI enablement team accountable for delivering the foundational capabilities required to scale AI within Large Molecule Discovery.

In this role, your core responsibilities include:

• Lead the transition of AI/ML models from research into production-ready solutions within LMD, ensuring successful integration into domain-specific scientific workflows and informatics systems
• Lead and develop a multidisciplinary team responsible for AI enablement, data standards, and workflow integration within the LMD ecosystem
• Drive adoption of AI/ML capabilities within LMD by defining and implementing research-to-production handoff patterns to implement machine learning models into end-to-end discovery workflows and enabling intuitive, reliable user experiences for scientists
• Provide clear priorities, coaching, and execution oversight to ensure delivery of high-quality, scalable capabilities across a diverse technical team
• Establish best practices for model reproducibility, documentation, governance, and compliance, aligned with enterprise standards and deployment frameworks
• Partner directly with experimental and computational scientists to identify high-impact opportunities for AI/ML integration and ensure solutions align with real-world scientific workflows
• Translate scientific research needs into clear technical, data, and workflow requirements, partnering with technology teams to deliver scalable, production-grade solutions
• Partner across scientific, data, and technology functions to ensure availability of high-quality, ML-ready datasets and robust data pipelines supporting LMD workflows