Senior MLOps Engineer — Edge Inference Platform

Hudl; United States; Remote; USD 140,000 - 180,000; Full time

Job summary

Hudl is hiring a Senior MLOps Engineer for the Hardware Group to build and scale ML infrastructure powering Focus, our line of smart cameras. You’ll own edge deployment pipelines delivering models to tens of thousands of devices globally and contribute to the platform that compiles models into optimized inference engines.

You will work with Data Scientists, Embedded Engineers and Product Managers to ensure smooth integration of features, drive automation, and build telemetry to monitor drift,

Qualifications

• Proven experience deploying ML models to edge devices.
• Experience with edge inference engines and model compilation.
• Familiarity with Python tooling and CI/CD practices.

Responsibilities

• Build scalable edge infrastructure and deployment systems for fleets of devices.
• Own the model compilation pipeline to produce hardware-specific engines.
• Collaborate with Data Scientists, Embedded Engineers and Product Managers.
• Drive automation, telemetry pipelines and monitoring for drift and latency.
• Develop resilient update mechanisms for low-bandwidth environments.
• Mentor the team on Python tooling, IaC, and CI/CD best practices.

Skills

MLOps

Edge deployment

Python

CI/CD

Infrastructure-as-Code

Telemetry

Tools

TensorRT

NVIDIA Jetson

Job description

Hudl is hiring a Senior MLOps Engineer for the Hardware Group to build and scale ML infrastructure powering Focus, our line of smart cameras. You’ll own edge deployment pipelines delivering models to tens of thousands of devices globally and contribute to the platform that compiles models into optimized inference engines.

You will work with Data Scientists, Embedded Engineers and Product Managers to ensure smooth integration of features, drive automation, and build telemetry to monitor drift,