At a Glance
- Tasks: Build and scale machine learning infrastructure for smart cameras in sports technology.
- Company: Join Hudl, a top-rated workplace focused on innovation and teamwork.
- Benefits: Enjoy flexible work options, competitive salary, and professional development opportunities.
- Why this job: Make an impact in sports tech while working with cutting-edge machine learning.
- Qualifications: Experience in MLOps, CI/CD, and collaboration with cross-functional teams required.
- Other info: Remote work available; great career growth in a supportive environment.
The predicted salary is between 48000 - 72000 ÂŁ per year.
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.
Your Role
We’re hiring a Senior MLOps Engineer to join our Hardware Group, where you’ll build and scale the machine learning infrastructure that powers our smart cameras, Focus. You’ll own the edge deployment pipelines that transport neural networks from training clusters to tens of thousands of devices globally and will act as the bridge between our Applied Machine Learning team in London and our Software squads in the Netherlands and the U.S., building the "nervous system" for the next generation of automated sports capture.
As a Senior MLOps Engineer, you’ll:
- Build scalable Edge infrastructure. You’ll design, develop, and maintain the delivery systems that enable us to deploy models to fleets of devices. You will lead the re-architecture to a dynamic, granular update system allowing faster learning.
- Work with cross-functional teams. You’ll collaborate with Data Scientists, Embedded Engineers and Product Managers to ensure smooth integration of complex features and capabilities, translating research requirements into deployable hardware realities.
- Drive automation and reliability. You’ll implement infrastructure to silently test candidate models on production devices, and build telemetry pipelines to monitor drift, thermal impact, and inference latency in the wild.
- Solve complex physical challenges. You’ll tackle the unique constraints of the edge—building resilient update mechanisms for low-bandwidth environments, optimising for limited storage, and ensuring devices recover gracefully from network failures.
- Mentor and lead. You’ll share your MLOps expertise to establish best practices in Python tooling, Infrastructure-as-Code, and CI/CD, guiding the team toward a more robust, automated future.
Must-Haves
- Experienced in production MLOps. You’ve played a key role in building and operating pipelines that deploy models to production—specifically dealing with the "physical world" (IoT, Edge, Robotics) rather than just cloud APIs.
- Technical expertise. You write clean, maintainable infrastructure code and have deep experience with CI/CD pipelines, containerization (Docker), and Linux systems.
- Collaborative. You understand that shipping to hardware is a team sport and can communicate effectively with researchers and low-level embedded engineers to translate constraints into solutions.
- Systems Thinking. You can design architectures that handle failure gracefully and understand the implications of deploying to 10,000 heterogeneous devices, including how to manage risk via canary releases and safe rollbacks.
- Bias towards action. You see your role as solving problems; this means filling gaps and taking initiative as needed to help the team win together.
Nice-to-Haves
- Edge AI Stack. Experience with the NVIDIA edge ecosystem (Jetson Nano/NX/Orin, DeepStream SDK, TensorRT) is a huge plus.
- Video Technologies. Familiarity with video pipelines, GStreamer, or ffmpeg.
- Fleet Management. Experience with tools like AWS IoT Greengrass, Balena, or custom OTA / fleet management solutions.
- Sports Passion. You have an interest in sports technology, video analytics, or performance metrics—but if not, we’ll teach you the domain.
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.
Compensation
The base salary range for this role is displayed below—starting salaries will typically fall near the middle of this range. We make compensation decisions based on an individual's experience, skills and education in line with our internal pay equity practices. This role will also be eligible for a long‑term incentive (LTI) award. Any bonuses awarded are based on individual and company performance paid at Hudl's discretion.
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.
Sr. MLOps Engineer - Hudl Focus New London or Remote (U.K.) employer: Hudl
Contact Detail:
Hudl Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr. MLOps Engineer - Hudl Focus New London or Remote (U.K.)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Hudl. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or any projects related to MLOps, make sure to highlight them during interviews. It’s all about demonstrating what you can bring to the table.
✨Tip Number 3
Prepare for technical challenges! Brush up on your knowledge of edge deployment and CI/CD pipelines. Be ready to discuss how you’d tackle real-world problems in the interview.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Hudl team.
We think you need these skills to ace Sr. MLOps Engineer - Hudl Focus New London or Remote (U.K.)
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior MLOps Engineer role. Highlight your experience with MLOps, especially in production environments, and how it relates to the unique challenges of deploying models to edge devices.
Showcase Your Technical Skills: Don’t hold back on your technical expertise! Mention your experience with CI/CD pipelines, containerisation, and any relevant tools like Docker or Linux systems. We want to see how you can contribute to building scalable edge infrastructure.
Emphasise Collaboration: Since this role involves working with cross-functional teams, share examples of how you've successfully collaborated with Data Scientists, Embedded Engineers, or Product Managers in the past. Show us that you understand the importance of teamwork in delivering complex features.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values!
How to prepare for a job interview at Hudl
✨Know Your MLOps Inside Out
Make sure you brush up on your MLOps knowledge, especially around edge deployment and CI/CD pipelines. Be ready to discuss your past experiences in deploying models to production, particularly in IoT or Edge environments, as this will show you understand the unique challenges of the role.
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, prepare examples of how you've successfully collaborated with Data Scientists, Embedded Engineers, and Product Managers. Highlight any specific projects where you translated complex requirements into practical solutions, as this will demonstrate your ability to communicate effectively across disciplines.
✨Demonstrate Systems Thinking
Be prepared to discuss how you approach designing architectures that handle failure gracefully. Think about examples where you've managed risks during deployments, such as canary releases or safe rollbacks, and be ready to explain your thought process behind these decisions.
✨Bring Your Passion for Sports Tech
While technical skills are crucial, showing a genuine interest in sports technology can set you apart. If you have any experience or personal projects related to video analytics or performance metrics, share those stories. If not, express your enthusiasm for learning about the domain and how it connects to your work.