Senior MLOps Engineer - Edge

Senior MLOps Engineer in Hudl's Hardware Group builds and scales ML infrastructure for Focus smart cameras. You’ll own edge deployment pipelines delivering models to thousands of devices and contribute to compiling models into hardware-optimised inference engines. You’ll collaborate with data scientists, embedded engineers, and product managers to ensure reliable, efficient edge AI. This role offers autonomy, impact on next-gen sports capture, and an inclusive, growth-focused culture.

• flexible vacation time
• remote work options
• company-wide holidays and timeout days
• medical and retirement benefits (location dependent)
• Employee Assistance Program
• employee resource groups

• Design, develop and maintain scalable edge infrastructure for model deployment to fleets of devices
• Own the model compilation platform and pipelines to generate hardware-specific inference engines (TensorRT, FP16/INT8, calibration, validation)
• Collaborate with Data Scientists, Embedded Engineers, and Product Managers to integrate complex features
• Implement automation and telemetry to monitor drift, thermal impact, and inference latency on production devices
• Develop resilient edge update mechanisms for low-bandwidth environments and manage canary releases/safe rollbacks
• Mentor and lead by sharing best practices in Python tooling, Infrastructure-as-Code, and CI/CD

• Production MLOps expertise with pipelines deploying models to production, CI/CD, Docker, Linux

• Collaborative communication with cross-functional teams
• Bias toward action and problem-solving initiative
• Systems thinking and risk management for large-scale deployments
• CI/CD
• Docker
• Linux