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- Tasks: Design and scale ML infrastructure for next-gen sports analytics.
- Company: Innovative tech company focused on sports metrics.
- Benefits: Remote work, supportive environment, and career growth opportunities.
- Why this job: Transform raw data into impactful insights in the sports industry.
- Qualifications: Extensive experience with ML systems and clean coding practices.
- Other info: Collaborate with cross-functional teams to drive efficiency through automation.
The predicted salary is between 43200 - 72000 £ per year.
A technology company is seeking a Senior MLOps Engineer to join its Global Football Metrics group. In this role, you'll design and scale the machine learning infrastructure for next-generation sports analytics, transforming raw data into production-ready insights. You will collaborate with cross-functional teams and drive efficiency through automation.
Ideal candidates will have extensive experience with ML systems, clean coding practices, and a focus on user needs. This position also offers a supportive work environment and opportunities for career growth.
Senior MLOps Engineer — Remote ML Pipelines for Sports in London employer: Hudl
Contact Detail:
Hudl Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLOps Engineer — Remote ML Pipelines for Sports in London
✨Tip Number 1
Network like a pro! Reach out to folks in the sports analytics and MLOps space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those related to ML systems and automation. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as collaboration is key in this role.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team and contributing to the exciting world of sports analytics.
We think you need these skills to ace Senior MLOps Engineer — Remote ML Pipelines for Sports in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ML systems and clean coding practices. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about sports analytics and how you can contribute to our Global Football Metrics group. Keep it engaging and personal.
Showcase Collaboration Skills: Since this role involves working with cross-functional teams, mention any past experiences where you’ve successfully collaborated with others. We love seeing teamwork in action!
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 us!
How to prepare for a job interview at Hudl
✨Know Your ML Systems Inside Out
Make sure you brush up on your knowledge of machine learning systems. Be ready to discuss your past experiences with ML pipelines, especially in sports analytics. Prepare examples that showcase how you've transformed raw data into actionable insights.
✨Showcase Your Clean Coding Practices
During the interview, be prepared to demonstrate your coding skills. Bring along examples of your clean code and explain your thought process behind it. This will highlight your attention to detail and commitment to quality, which is crucial for this role.
✨Emphasise Collaboration and Automation
Since this role involves working with cross-functional teams, be ready to talk about your experience collaborating with others. Share specific instances where you drove efficiency through automation, as this will show your ability to enhance team performance.
✨Align with User Needs
Understand the importance of user needs in the context of sports analytics. Be prepared to discuss how you've previously focused on user requirements in your projects. This will demonstrate that you can create solutions that truly benefit end-users.
