Senior MLOps Engineer or United Kingdom - Remote

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.

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. 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 across the full ML lifecycle.
• Work with cross-functional teams. 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. 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. 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. Share your MLOps expertise to establish best practices and guide other engineers on topics such as model versioning, experiment tracking and feature stores.

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.

• Experience in production ML systems. Play 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. Write clean, maintainable code, follow software engineering best practices, and have hands‑on experience with containerisation, orchestration tools, CI/CD pipelines, and infrastructure‑as‑code.
• Collaborative. Work effectively with cross‑functional partners to translate requirements into scalable solutions.
• User‑focused. Build systems that help real people solve real problems, caring about the experience of both internal data scientists and external customers.

• MLOps tooling experience. Experience with MLflow, Kubeflow, Airflow, Feast, DVC, Weights & Biases or similar ML platforms.
• Tech stack knowledge.
  
  Experience with Python, Kafka, Postgre
  
  SQL, Redshift, S3, Sage Maker or AWS infrastructure.
• Sports analytics passion. Interest in sports data, video analytics or performance metrics.

• Champion work‑life harmony. Flexible vacation time, company‑wide holidays, meeting‑free days, remote work options and more.
• Guarantee autonomy. Open, honest culture with trust from day one; ownership of work and agency to try new ideas.
• Encourage career growth. Lifelong learning culture, resources and opportunities to keep growing.
• Provide an environment to help you succeed. Invested offices, technology for remote or in‑office work.
• Support your wellbeing. Medical and retirement benefits (depending on location), Employee Assistance Program and employee resource groups.

Hudl is an equal opportunity employer. We create an environment where everyone, no matter their differences, feels like they belong. We offer resources—employee resource groups, communities, and ongoing inclusion reports—to support safety, authenticity and growth. We also recognize imposter syndrome and confidence gaps, and we encourage you to apply.