Head of Technical Programme Management

The Technical Program Manager is not expected to code models, but must have sufficient technical depth to drive execution, manage trade‑offs, and unblock teams working on Linux‑based vision systems, sensors, PLC‑integrated environments, and real‑time data pipelines.

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

APIs and backend platform services

Coordinate validation in industrial or field environments, managing constraints like latency, hardware limitations, and environmental variability

Risk, Metrics & Delivery Excellence

Identify risks related to:

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

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

Demonstrated ability to manage cross‑functional technical programs involving software, hardware, and data pipelines

Experience with edge AI deployments (Jetson, embedded GPUs, industrial edge devices)

Familiarity with Amazon SageMaker workflows for model training and tuning

Experience delivering systems that integrate ML outputs into APIs, dashboards, or operational UIs

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