Senior Technical Program Manager, Health ML

RESPONSIBILITIES:

• Own end-to-end program management for health algorithm development initiatives, from early research and data collection through model development, validation, regulatory submission, and production deployment

• Partner with leadership to translate health feature strategy into executable program plans with clear milestones, dependencies, risk profiles, and success criteria

• Plan and manage ML development timelines with full awareness of cross-functional dependencies across data engineering, clinical, regulatory, quality, software, firmware, and product teams

• Drive cross-functional alignment by working directly with program managers and leads on partner teams to ensure shared understanding of priorities, timelines, and deliverables

• Proactively identify future risks, obstacles, and dependencies before they become blockers; develop and drive mitigation plans

• Report program status, risks, and key decisions to leadership with clarity and precision; flag issues early and with proposed solutions

• Facilitate and maintain program governance including planning cadences, design reviews, decision forums, and cross-team syncs

• Oversee health data governance workflows relevant to ML development, including data collection, labeling, dataset management, and data quality processes

• Build and continuously improve AI-enabled tools, workflows, and automations to increase program management effectiveness, including status tracking, dependency mapping, risk monitoring, and stakeholder communication

QUALIFICATIONS:

• 5+ years of experience in an ML role or technical program management, with direct experience supporting AI/ML, data science, or algorithm development teams

• Demonstrated understanding of the ML development lifecycle, including data collection, model training, evaluation, validation, and deployment

• Experience with developing algorithms for Software as a Medical Device (SaMD), medical device development, or other regulated product development (FDA, IEC 62304, ISO 13485, ISO 14971)

• Fluency with AI tools (e.g., LLMs, automation platforms, workflow builders) and a demonstrated track record of building or adopting AI-powered workflows to increase speed and scale of program execution

• Ability to understand technical concepts deeply enough to identify risks, ask critical questions, and facilitate resolution of blockers across ML, data, software, and regulatory workstreams

• Clear, confident communicator who can bridge deeply technical ML teams and business, regulatory, and clinical stakeholders

• Data-driven approach to program planning and tracking, comfortable defining and reviewing metrics to measure program health and success