Senior MLOps Engineer - Football Metrics in London
Senior MLOps Engineer - Football Metrics

Senior MLOps Engineer - Football Metrics in London

London Full-Time 30000 - 50000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Build and scale machine learning infrastructure for next-gen sports analytics.
  • Company: Join Hudl, a top-rated workplace dedicated to innovation and teamwork.
  • Benefits: Flexible work hours, remote options, and professional development opportunities.
  • Why this job: Make a real impact in sports analytics while working with cutting-edge technology.
  • Qualifications: Experience in production ML systems and collaborative team skills required.
  • Other info: Enjoy a supportive culture that values work-life balance and personal growth.

The predicted salary is between 30000 - 50000 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 Global Football Metrics group, where you'll build and scale the machine learning infrastructure that powers next‐generation sports analytics. You'll own the MLOps pipelines that transform raw data and ML models into production‐ready insights used by professional teams worldwide.

As a Senior MLOps Engineer, You'll:

  • Build scalable ML infrastructure. You'll design, develop and maintain the MLOps platforms and pipelines that enable our data science teams to train, deploy and monitor machine learning models at scale while working across the full ML lifecycle.
  • Work with cross‐functional teams. You'll collaborate with Data Scientists, ML Engineers, Software Engineers, Product and Platform teams to deliver robust, automated ML systems that bridge the gap between research and production.
  • Drive automation and efficiency. You'll implement CI/CD pipelines for ML models, automate retraining workflows and build monitoring systems to ensure reliability as you deploy changes hundreds of times daily.
  • Solve complex technical challenges. You'll tackle ambiguous infrastructure problems, evaluate new MLOps tools and architect solutions that enable our data science teams to work faster and more effectively.
  • Mentor and lead. You'll share your MLOps expertise to establish best practices and guide other engineers on topics like model versioning, experiment tracking and feature stores.

Must‐Haves:

  • Experienced in production ML systems. You've played a key role in building and operating large‐scale machine learning infrastructure and understand the challenges of moving models from notebooks to production.
  • Technical expertise. You write clean, maintainable code and understand software engineering best practices, plus you have hands‐on experience with containerisation, orchestration tools, CI/CD pipelines, and infrastructure‐as‐code.
  • Collaborative. You understand that building ML systems is a team sport and work effectively with cross‐functional partners to translate requirements into scalable solutions.
  • User‐focused. You're motivated by building systems that help real people solve real problems, caring about the experience of both internal data scientists and external customers.

Nice‐to‐Haves:

  • MLOps tooling experience. Experience with MLflow, Kubeflow, Airflow, Feast, DVC, Weights & Biases or similar ML platforms would be great.
  • Tech stack knowledge. Experience with Python, Kafka, PostgreSQL, Redshift, S3, SageMaker or AWS infrastructure is a plus.
  • Sports analytics passion. You have an interest in sports data, 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.

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.

Senior MLOps Engineer - Football Metrics in London employer: Hudl

Hudl is an exceptional employer that fosters a culture of collaboration and innovation, allowing employees to thrive in their roles while enjoying the flexibility of remote work options and generous vacation policies. With a strong commitment to professional development and employee wellbeing, Hudl provides a supportive environment where you can grow your skills and contribute to cutting-edge sports analytics technology. Join us in making a meaningful impact in the world of sports, surrounded by passionate colleagues who are dedicated to excellence.
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Contact Detail:

Hudl Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior MLOps Engineer - Football Metrics in London

✨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 GitHub with projects related to MLOps, make sure to highlight them. Real-world examples of your work can speak volumes.

✨Tip Number 3

Prepare for the interview by brushing up on your technical knowledge and soft skills. Be ready to discuss how you've tackled challenges in past roles and how you can contribute to the team at Hudl.

✨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 Senior MLOps Engineer - Football Metrics in London

MLOps
Machine Learning Infrastructure
CI/CD Pipelines
Containerisation
Orchestration Tools
Infrastructure-as-Code
Python
Data Analysis
Collaboration
MLflow
Kubeflow
Airflow
PostgreSQL
AWS Infrastructure
Sports Analytics

Some tips for your application 🫡

Show Your Passion for MLOps: When you're writing your application, let us see your enthusiasm for MLOps and sports analytics. Share any relevant projects or experiences that highlight your skills and passion for the field. We love candidates who are genuinely excited about what they do!

Tailor Your Application: Make sure to customise your CV and cover letter to match the job description. Highlight your experience with ML systems, CI/CD pipelines, and any tools mentioned in the posting. This shows us you’ve done your homework and understand what we’re looking for.

Be Clear and Concise: Keep your application straightforward and to the point. Use bullet points where possible to make it easy for us to read through your qualifications. We appreciate clarity and want to quickly see how you fit into our team!

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’s super easy—just follow the prompts and you’ll be set!

How to prepare for a job interview at Hudl

✨Know Your MLOps Inside Out

Make sure you brush up on your knowledge of MLOps tools and practices. Familiarise yourself with platforms like MLflow, Kubeflow, and CI/CD pipelines. Being able to discuss your hands-on experience with these tools will show that you're ready to hit the ground running.

✨Showcase Your Collaboration Skills

Since this role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you translated complex technical requirements into scalable solutions, as this will demonstrate your ability to work effectively with others.

✨Prepare for Technical Challenges

Expect to tackle some tricky technical questions during your interview. Brush up on your problem-solving skills and be ready to discuss how you've approached ambiguous infrastructure problems in the past. This will help you stand out as someone who can think critically and creatively.

✨Express Your Passion for Sports Analytics

Even if you don't have a deep background in sports analytics, showing enthusiasm for the field can make a big difference. Share any personal interests or experiences related to sports data or performance metrics, and be open to learning more about the domain. This will demonstrate your motivation to contribute to the team.

Senior MLOps Engineer - Football Metrics in London
Hudl
Location: London

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