Technical Program Manager

Program Ownership & Execution

Own end-to-end delivery of computer vision programs, from requirements definition through edge deployment and production rollout

Break down complex CV initiatives (model training, fine-tuning, inference optimization, edge rollout) into clear milestones, timelines, and dependencies

Manage cross-team dependencies across ML, embedded/edge, hardware, industrial systems, and UI/API teams

Technical Program Leadership (Computer Vision Focus)

• Partner with Computer Vision Engineers building YOLO/CNN-based models to align on execution plans, performance targets, and deployment readiness
• Drive coordination across teams deploying models on Raspberry Pi, Jetson Nano, CPU/GPU edge platforms
• Manage programs involving Linux systems, sensors, industrial cameras, PLC-connected devices, and real-time data streams
• Ensure model training and tuning workflows using Amazon SageMaker are production-ready and aligned to delivery timelines
• Edge & Industrial Integration
• Drive programs that integrate vision outputs into:
• Dashboards and operational tools
• APIs and backend platform services
• UI and downstream consuming teams
• Coordinate validation in industrial or field environments, managing constraints like latency, hardware limitations, and environmental variability
• Risk, Metrics & Delivery Excellence
• Identify risks related to:
• Model accuracy vs. inference performance
• Edge hardware constraints
• Data quality, sensor reliability, and real-time processing
• Define and track program metrics such as model readiness, deployment success rates, latency targets, and operational stability
• Escalate issues early and drive data-based trade-off decisions
• Communication & Stakeholder Management
• Communicate program status, risks, and decisions clearly to senior technical and business stakeholders
• Serve as the single-threaded owner for Computer Vision programs across multiple teams
• Translate engineer-level detail into executive-level updates

3-5+ years of experience in technical program management or systems program management

Experience working with computer vision, ML systems, edge computing, or embedded systems teams

Strong understanding of:

• Linux environments
• Camera/sensor-based systems
• Model training vs. inference trade-offs
• Demonstrated ability to manage cross-functional technical programs involving software, hardware, and data pipelines
• Strong written and verbal communication skills, * Experience with edge AI deployments (Jetson, embedded GPUs, industrial edge devices)
• Familiarity with Amazon SageMaker workflows for model training and tuning
• Exposure to industrial systems, PLC-integrated environments, or real-time streaming architectures
• Experience delivering systems that integrate ML outputs into APIs, dashboards, or operational UIs