Senior MLOps Engineer - Edge
Core
Build and scale machine learning infrastructure to deploy neural networks to tens of thousands of edge devices globally, optimizing inference engines for automated sports capture.
Role type
Senior MLOps Engineer (Edge AI)
Builds
Edge deployment pipelines, model compilation platforms, and telemetry systems for smart cameras.
Domain
Sports technology / Edge AI / Embedded Systems
Deliverable
production ML models
Required skills
MLOps, CI/CD, containerization, Linux systems, model compilation, TensorRT, precision trade-offs, engine validation, canary releases, safe rollbacks, Python tooling, Infrastructure-as-Code
Preferred skills
NVIDIA Jetson Orin, DeepStream SDK, GStreamer, ffmpeg, AWS IoT Greengrass, Balena, OTA fleet management
Technologies
Docker, TensorRT, Linux, Python, Jetson Orin, DeepStream SDK, GStreamer, ffmpeg, AWS IoT Greengrass, Balena
Responsibilities
Design and maintain delivery systems for deploying models to device fleets; build pipelines for compiling trained models into optimized inference engines; implement infrastructure for testing models on production devices and monitoring telemetry; develop resilient update mechanisms for low-bandwidth environments; mentor team on best practices for tooling and CI/CD.
Seniority
Senior, hands-on IC
