Hudl is hiring an Engineering Manager - MLOps & Edge Infrastructure

Hudl is hiring an Engineering Manager - MLOps & Edge Infrastructure to lead a new team that bridges AI research and smart cameras. You will own the MLOps infrastructure for autonomous tracking features, spending about 1/3 of your time hands-on architecting solutions and 2/3 of your time managing and guiding the team.

What You'll Do

• Own the pipeline from Cloud to Edge, re-architecting how machine learning models are deployed to tens of thousands of edge devices.
• Lead the move from monolithic firmware packages to a dynamic, granular model delivery system.
• Build 'shadow mode' infrastructure to test candidate models on production devices silently.
• Drive governance and monitoring by building tooling to monitor model drift, performance metrics, and health signals from the edge.
• Hire and manage a team of Senior to Mid-level Engineers, fostering a culture of technical excellence and agile delivery.
• Own and shape the team's roadmap and partner with Embedded and AI/ML teams to remove friction between model training and device inference.

What We're Looking For

• MLOps expertise with a proven track record of building and managing pipelines that deploy ML models to production.
• Understanding of the unique challenges of Edge AI / IoT versus cloud-only deployments.
• Strong Python skills, comfortable writing robust scripts, building automation tools, and handling infrastructure-as-code.
• Strategic engineering leadership experience managing engineers, running technical design reviews, and breaking down complex projects.
• Ability to define system architecture, architect resilient update mechanisms, and understand concepts like delta updates and event-based systems.

Nice to Have

• Edge model deployment infrastructure experience solving problems related to deploying, monitoring, and maintaining models on edge devices.
• Experience with NVIDIA Jetson / DeepStream and the NVIDIA edge ecosystem (Nano, NX, Orin).
• Experience with video streaming technology like GStreamer, video encoding, or camera ISPs.
• Containerisation & orchestration know-how with Docker and container orchestration on embedded devices.

Technical Stack

• Python
• MLOps
• Edge AI
• IoT
• NVIDIA Jetson
• DeepStream
• GStreamer
• Docker

Team & Environment

You'll lead a squad of engineers and be part of the London AI/ML organization, partnering closely with the Embedded squad in the Netherlands.

Benefits & Compensation

• Flexible vacation time above statutory leave.
• Company-wide holidays and timeout (meeting-free) days.
• Remote work options.
• Resources and opportunities for professional development.
• Investment in office spaces and provision of tech for remote work.
• Medical and retirement benefits (location-dependent).
• Employee Assistance Program and employee resource groups for mental health support.

Work Mode

This is a hybrid role based in London, UK.

Hudl is an equal opportunity employer. Through our actions, behaviors and attitude, we’ll create an environment where everyone, no matter their differences, feels like they belong.