At a Glance
- Tasks: Build and scale machine learning infrastructure for next-gen sports analytics.
- Company: Join Hudl, a top-rated workplace dedicated to teamwork and innovation.
- Benefits: Flexible work options, competitive salary, and resources for professional growth.
- Why this job: Make an 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 harmony and personal wellbeing.
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 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.
- 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.
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 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, 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.
Senior MLOps Engineer - Football Metrics in Liverpool employer: Hudl
Contact Detail:
Hudl Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLOps Engineer - Football Metrics in Liverpool
✨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 GitHub with projects related to MLOps, make sure to highlight them during interviews. Real-world examples speak volumes!
✨Tip Number 3
Prepare for technical challenges! Brush up on your problem-solving skills and be ready to tackle some tricky questions. Practice makes perfect, so don’t skip this step!
✨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 Senior MLOps Engineer - Football Metrics in Liverpool
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 ML infrastructure and any relevant projects that showcase your skills in building scalable systems.
Showcase Collaboration Skills: Since this role involves working with cross-functional teams, don’t forget to mention your teamwork experiences. Share examples of how you’ve collaborated with data scientists or engineers to deliver successful projects.
Demonstrate Technical Expertise: Be specific about your technical skills! Mention your experience with containerisation, CI/CD pipelines, and any MLOps tools you’ve used. This will show us that you’re ready to hit the ground running.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to see your application and get to know you better. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Hudl
✨Know Your MLOps Inside Out
Make sure you’re well-versed in the MLOps tools and practices mentioned in the job description. Brush up on your experience with CI/CD pipelines, containerisation, and orchestration tools. Being able to discuss specific projects where you've implemented these will show you're the real deal.
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, prepare examples of how you've successfully collaborated with data scientists, engineers, or product teams in the past. Highlighting your ability to translate complex requirements into scalable solutions will set you apart.
✨Demonstrate Your Problem-Solving Abilities
Be ready to tackle some technical challenges during the interview. Think of a few ambiguous infrastructure problems you've solved and be prepared to discuss your thought process. This will showcase your analytical skills and your ability to think on your feet.
✨Express Your Passion for Sports Analytics
Even if you don’t have extensive experience in sports analytics, showing genuine interest can go a long way. Share any relevant experiences or projects that relate to sports data or performance metrics, and express your eagerness to learn more about the domain.