Engineering Manager - MLOps & Edge Infrastructure
At Hudl, we build great teams. We hire the best of the best to ensure you’re working with people you can constantly learn from. You’re trusted to get your work done your way while testing the limits of what’s possible and what’s next. We work hard to provide a culture where everyone feels supported, and our employees feel it—their votes helped us become one of Newsweek's Top 100 Global Most Loved Workplaces.
We think of ourselves as the team behind the team, supporting the lifelong impact sports can have: the lessons in teamwork and dedication; the influence of inspiring coaches; and the opportunities to reach new heights. That’s why we help teams from all over the world see their game differently. Our products make it easier for coaches and athletes at any level to capture video, analyze data, share highlights and more.
Ready to join us?
Your Role
We’re hiring an Engineering Manager to lead a brand new team in London bridging the gap between our state-of-the-art AI research and our industry-leading smart cameras, Focus. You’ll lead a specialised squad of engineers responsible for the MLOps infrastructure that powers "Tactical View" and next-generation autonomous tracking features.
As a player-coach, you’ll spend roughly one-third of your time hands-on—architecting solutions and writing tooling—and two-thirds of your time managing and strategically guiding your team. You’ll be directly responsible for owning and shaping the roadmap as well as partnering with our Embedded squad in the Netherlands and the London AI/ML org to remove friction between model training and device inference.
In this role, you'll:
- Own the pipeline from Cloud to Edge: You’ll re-architect how we deploy machine learning models to tens of thousands of edge devices. You will lead the move from monolithic firmware packages to a dynamic, granular model delivery system.
- Build "shadow mode" Infrastructure: You’ll design and implement the systems that allow us to test candidate models on production devices silently, enabling data-driven decisions on accuracy and performance before a full rollout.
- Drive governance and monitoring: You’ll build the tooling to monitor model drift, performance metrics, and health signals from the edge, ensuring our automated capture systems remain reliable across different sports and environments.
- Lead and mentor: Hire and manage a team of Senior to Mid-level Engineers. You will foster a culture of technical excellence, agile delivery, and continuous improvement, following best practices.
We'd like to hire someone for this role who lives near our office in London, but we're also open to remote candidates in the UK . Remote candidates would have the ability to work from a co-working space or their home.
Must-Haves
- MLOps expertise: You have a proven track record of building and managing pipelines that deploy ML models to production. You understand the unique challenges of Edge AI / IoT versus cloud-only deployments.
- Strong Python skills: You’re comfortable jumping into the codebase and can write robust Python scripts, build automation tools, and handle infrastructure-as-code.
- Strategic engineering leadership: You have experience managing engineers, running technical design reviews, and breaking down complex long-term projects into executable milestones.
- Ability to define system architecture: You can architect resilient update mechanisms. You understand concepts like delta updates, event based systems, and modern approaches to challenges at scale.
Nice-to-Haves
- Edge model deployment infrastructure: you’ve solved the problems related to creating infrastructure which deploys, monitors, and maintains models on edge devices.
- Experience with NVIDIA Jetson / DeepStream: It would be great if you have familiarity with the NVIDIA edge ecosystem (Nano, NX, Orin) and the DeepStream SDK.
- Experience with video streaming technology: Knowledge of GStreamer, video encoding, or camera ISPs would be beneficial.
- Containerisation & orchestration know-how: Experience with Docker and container orchestration on embedded devices is a plus.
Our Role
- Champion work-life harmony. We’ll give you the flexibility you need in your work life (e.g., flexible vacation time above any required statutory leave, company-wide holidays and timeout (meeting-free) days, remote work options and more) so you can enjoy your personal life too.
- Guarantee autonomy. We have an open, honest culture and we trust our people from day one. Your team will support you, but you’ll own your work and have the agency to try new ideas.
- Encourage career growth. We’re lifelong learners who encourage professional development. We’ll give you tons of resources and opportunities to keep growing.
- Provide an environment to help you succeed. We've invested in our offices, designing incredible spaces with our employees in mind. But whether you’re at the office or working remotely, we’ll provide you the tech you need to do your best work.
- Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees—but no matter where you’re located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health.
Inclusion at Hudl
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.
We offer resources to ensure our employees feel safe bringing their authentic selves to work, including employee resource groups and communities. But we recognize there’s ongoing work to be done, which is why we track our efforts and commitments in annual inclusion reports.
We also know imposter syndrome is real and the confidence gap can get in the way of meeting spectacular candidates. Please don’t hesitate to apply—we’d love to hear from you.
