Fast Facts
Join as an Engineering Manager to lead a new team in London focusing on MLOps infrastructure for AI-driven smart cameras, blending hands-on coding with strategic leadership.
Responsibilities: Oversee the integration and deployment of ML models across edge devices, manage a team of engineers, and establish governance for model performance monitoring.
Skills: MLOps expertise, strong Python coding skills, and strategic engineering leadership are essential for success.
Qualifications: Experience with edge model deployment infrastructure and familiarity with NVIDIA ecosystem tools is preferred.
Location: London, UK, with remote options available.
Compensation: Not provided by employer. Typical compensation ranges for this position are between £90,000 - £130,000.
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.
