Sr. MLOps Engineer - Hudl Focus
Sr. MLOps Engineer - Hudl Focus

Sr. MLOps Engineer - Hudl Focus

Full-Time 64000 - 111000 ÂŁ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Build and scale machine learning infrastructure for smart cameras in sports technology.
  • Company: Join Hudl, a top-rated workplace dedicated to 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 AI and a passionate team.
  • Qualifications: Experience in MLOps, strong coding skills, and a collaborative mindset are essential.
  • Other info: Remote work available; we support your growth and well-being.

The predicted salary is between 64000 - 111000 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.

Responsibilities

  • 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.

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.

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. Base Salary Range £64,000 — £111,000 GBP.

Inclusion at Hudl

Hudl is an equal opportunity employer. Through our actions, behaviours 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 employer: Hudl

At Hudl, we pride ourselves on fostering a supportive and innovative work culture that empowers our employees to excel. As a Senior MLOps Engineer, you'll enjoy flexible working arrangements, ample opportunities for professional growth, and the chance to collaborate with talented teams across the globe, all while contributing to the exciting world of sports technology. Our commitment to employee wellbeing and inclusion ensures that everyone feels valued and can thrive in their roles.
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Hudl Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Sr. MLOps Engineer - Hudl Focus

✨Tip Number 1

Network like a pro! Reach out to folks 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 that highlight your MLOps expertise, make sure to share them during interviews. It’s all about proving you can walk the walk.

✨Tip Number 3

Prepare for the technical grill! Brush up on your knowledge of CI/CD pipelines, containerization, and edge deployment. Be ready to discuss how you’ve tackled similar challenges in the past.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. 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

MLOps
Edge Infrastructure
CI/CD Pipelines
Containerization (Docker)
Linux Systems
Collaboration
Systems Thinking
Problem-Solving
NVIDIA Edge Ecosystem (Jetson Nano/NX/Orin, DeepStream SDK, TensorRT)
Video Technologies (GStreamer, ffmpeg)
Fleet Management (AWS IoT Greengrass, Balena)
Python Tooling
Infrastructure-as-Code

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 production MLOps, especially in IoT and Edge environments, to show us you’re the perfect fit!

Showcase Your Technical Skills: Don’t hold back on your technical expertise! We want to see your experience with CI/CD pipelines, containerisation, and Linux systems. Use specific examples to demonstrate how you've tackled challenges in these areas.

Emphasise Collaboration: Since this role involves working with cross-functional teams, share examples of how you’ve successfully collaborated with Data Scientists and Engineers in the past. We love a team player who can communicate effectively!

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 don’t miss out on any important updates from our team!

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 deploying models to production. Be ready to discuss your experience with edge devices and how you've tackled challenges in the physical world, as this is crucial for the role.

✨Showcase Your Collaboration Skills

Since this role involves working closely with Data Scientists and Embedded Engineers, prepare examples of how you've successfully collaborated in the past. Highlight your ability to translate complex technical requirements into practical solutions that benefit the whole team.

✨Demonstrate Systems Thinking

Be prepared to discuss how you approach designing architectures that handle failure gracefully. Think about your experiences with canary releases and safe rollbacks, and be ready to share specific examples of how you've managed risk in large-scale deployments.

✨Bring Your Passion for Sports Technology

While it's not a must-have, showing a genuine interest in sports technology or video analytics can set you apart. If you have any personal projects or experiences related to this field, be sure to mention them during the interview to demonstrate your enthusiasm.

Sr. MLOps Engineer - Hudl Focus
Hudl
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  • Sr. MLOps Engineer - Hudl Focus

    Full-Time
    64000 - 111000 ÂŁ / year (est.)
  • H

    Hudl

    201-500
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