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Your Role:
- Build scalable edge infrastructure for deploying ML models to tens of thousands of devices.
- Own the model compilation pipeline, managing TensorRT compilation and precision optimization.
- Drive automation, telemetry, and resilient update mechanisms for edge deployments.
Must-Haves:
- Production MLOps expertise with CI/CD, Docker, and Linux systems.
- Hands-on TensorRT experience for embedded hardware inference.
- Strong collaboration and systems thinking for handling heterogeneous fleets.
Nice-to-Haves:
- Experience with NVIDIA Jetson Orin, DeepStream, and video pipelines (GStreamer/ffmpeg).
- Fleet management tools like AWS IoT Greengrass or Balena.
- Passion for sports technology or video analytics.
Hudl
Hudl provides video analysis and data tools that help sports teams and athletes improve their performance. The company fosters a collaborative culture and has been named one of Newsweek's Top 100 Global Most Loved Workplaces.