Senior MLOps Engineer - Edge AI for Smart Cameras (Remote)

Hudl; United Kingdom; Hybrid; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Flexible work options

Remote work options

Medical benefits

Job summary

Hudl in London or Barcelona is seeking a Senior MLOps Engineer for our Hardware Group to build and scale the ML infrastructure powering Focus, our line of smart cameras. You’ll own edge deployment pipelines delivering models to tens of thousands of devices globally.

You'll collaborate with Data Scientists, Embedded Engineers and Product Managers to ensure reliable, hardware-optimised inference engines, and drive automation, monitoring, and canary rollouts for a robust edge ecosystem.

Qualifications

• Production MLOps pipelines for production deployments.
• Experience with CI/CD, containerization (Docker) and Linux systems.
• Edge compilation and optimisation for embedded hardware (TensorRT).

Responsibilities

• Build scalable edge infrastructure to deploy models to fleets of devices.
• Own the model compilation platform to create hardware-specific inference engines.
• Collaborate with data scientists, embedded engineers, and product managers.
• Drive automation and telemetry to monitor drift, latency and reliability.
• Design resilient edge architectures with canary releases and safe rollbacks.
• Mentor team on Python tooling, IaC, and CI/CD best practices.

Skills

Production MLOps

Edge inference

CI/CD

Docker

Linux systems

TensorRT

Collaboration

Systems thinking

Tools

Jetson Orin

DeepStream SDK

TensorRT

Job description

Hudl in London or Barcelona is seeking a Senior MLOps Engineer for our Hardware Group to build and scale the ML infrastructure powering Focus, our line of smart cameras. You’ll own edge deployment pipelines delivering models to tens of thousands of devices globally.

You'll collaborate with Data Scientists, Embedded Engineers and Product Managers to ensure reliable, hardware-optimised inference engines, and drive automation, monitoring, and canary rollouts for a robust edge ecosystem.