Technical Engagement Manager – AI/ML (HealthCare)

About the role

Technical Engagement Manager leading AI/ML deployments in medical device environments. Drives discovery, translates video analytics use cases, scopes model development, and delivers commercial proposals. Manages cross-functional engineering POD on-premises, ensuring regulatory compliance and stakeholder communication.

What you’ll do

• Serve as primary contact among client sales, customers, and engineering POD
• Lead discovery, on-site observation, and requirement gathering for video ML
• Translate workflows and challenges into structured AI/ML use cases
• Scope model dev, data prep, and validation with data scientists and ML engineers
• Drive full lifecycle of engagement from opportunity to delivery and success
• Ensure technical alignment, risk mgmt, and timeline adherence across teams
• Shape and present commercial proposals, ROI, roadmaps, and value narratives
• Manage stakeholder communication, reporting, and executive updates
• Ensure compliance with healthcare/medical device regulatory standards for video data
• Promote experimentation, rapid iteration, hypothesis-driven development within POD

What you’ll bring

• 8+ yrs customer-facing delivery, program mgmt, or AI/ML engagement leadership
• Strong ML knowledge: video analytics, computer vision, supervised workflows
• Experience in healthcare, medical devices, or regulated environments with sensitive data
• Translate ambiguous customer needs into well-scoped technical requirements
• Excellent communication, storytelling, and client management skills
• Proven on-premises discovery and solution design with customers
• Strong commercial acumen: pricing, proposal creation, value-modeling
• Lead cross-functional engineering teams in dynamic, field-deployed setting

Nice to have

• Background in data science, computer vision, or ML engineering
• Prior experience in forward deployment, field engineering, or consulting
• Knowledge of FDA/medical device regulatory frameworks
• Familiarity with video annotation tools, model training pipelines, edge-deployment workflows

Skills