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Hudl

Senior MLOps Engineer - Edge

Barcelona
Posted about 12 hours ago
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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 a Senior MLOps Engineer for our Hardware Group to build and scale the machine learning infrastructure that powers Focus, our line of smart cameras. You'll own the edge deployment pipelines that transport neural networks from training clusters to tens of thousands of devices globally, and contribute to the platform that compiles trained models into optimized inference engines for devices like the Jetson Orin, 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.
  • Own the model compilation platform. You'll build and maintain the pipeline that takes trained models and produces optimized, hardware-specific inference engines — managing TensorRT compilation, precision trade-offs (FP16/INT8), calibration, and engine validation to ensure models run reliably and efficiently on target devices.
  • 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.
  • 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, optimizing for limited storage, and ensuring devices recover gracefully from network failures.
  • Mentor and lead. You'll share your expertise to establish best practices in Python tooling, Infrastructure-as-Code, and CI/CD, guiding the team toward a more robust, automated future.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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It searches the market for you

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

We'd like to hire someone for this role who lives near our offices in London or Barcelona, but we're also open to remote candidates in the UK and Spain.

Must-Haves

  • Production MLOps expertise. You've played a key role in building and operating pipelines that deploy models to production, with deep experience in CI/CD, containerization (Docker), and Linux systems.
  • Edge inference & compilation know-how. You have hands-on experience compiling and optimizing models for embedded hardware - ideally with TensorRT - and understand the practical implications of precision, quantisation, and engine validation at scale.
  • 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

  • Experience with our Edge AI stack. Experience with the NVIDIA edge ecosystem (Jetson 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.

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Our Role

  • Champion work-life harmony. We’ll give you the flexibility you need in your work life (e.g., flexible vacation time, 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 stack and hardware 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

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.

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Skills

MLOps
Python
Docker
TensorRT
CI/CD
Linux
Edge AI
Infrastructure-as-Code
Model compilation
Embedded systems
AWS IoT Greengrass
Balena
GStreamer
FFmpeg
Telemetry
Automation

Location

Barcelona, Catalonia, Spain

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