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- Tasks: Build scalable ML infrastructure and support data science teams with MLOps pipelines.
- Company: Leading sports analytics company with a focus on innovation.
- Benefits: Remote work, flexibility, career growth, and a supportive environment.
- Why this job: Join a dynamic team and make an impact in the world of sports analytics.
- Qualifications: Strong production ML experience and collaborative skills.
The predicted salary is between 48000 - 72000 £ per year.
A leading sports analytics company is looking for a Senior MLOps Engineer to build scalable ML infrastructure and support data science teams. You will own MLOps pipelines, work with cross-functional teams to automate systems, and implement CI/CD workflows. Ideal candidates will have strong production ML experience and a collaborative spirit. The position permits remote work within the UK, offering flexibility, career growth, and a supportive work environment.
Senior MLOps Engineer: Scale ML Infrastructure (Remote UK) in London employer: Hudl
Contact Detail:
Hudl Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLOps Engineer: Scale ML Infrastructure (Remote UK) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the sports analytics and MLOps space on LinkedIn. Join relevant groups and engage in discussions; you never know who might have a lead on that perfect role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially those involving CI/CD workflows. This will give potential employers a taste of what you can bring to their team.
✨Tip Number 3
Prepare for interviews by brushing up on common MLOps challenges and solutions. Be ready to discuss how you've tackled similar issues in the past, and don’t forget to highlight your collaborative spirit!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to reflect your passion for building scalable ML infrastructure and supporting data science teams.
We think you need these skills to ace Senior MLOps Engineer: Scale ML Infrastructure (Remote UK) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your production ML experience and any relevant projects you've worked on. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and collaborative spirit. Share why you’re excited about the role and how you can contribute to our team. Keep it engaging and relevant!
Showcase Your MLOps Knowledge: Since this role focuses on building scalable ML infrastructure, make sure to mention any specific tools or frameworks you’ve used. We love seeing candidates who are up-to-date with the latest trends in MLOps!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to shine in front of our hiring team!
How to prepare for a job interview at Hudl
✨Know Your ML Infrastructure
Make sure you brush up on your knowledge of scalable ML infrastructure. Be ready to discuss your experience with MLOps pipelines and how you've automated systems in the past. This will show that you understand the technical requirements of the role.
✨Showcase Collaboration Skills
Since the job involves working with cross-functional teams, prepare examples of how you've successfully collaborated with others. Highlight any projects where teamwork was key to achieving results, as this will demonstrate your collaborative spirit.
✨Be Ready for Technical Questions
Expect to face some technical questions related to CI/CD workflows and production ML. Brush up on best practices and be prepared to explain your thought process when solving problems. This will help you stand out as a knowledgeable candidate.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to sports analytics and their future plans for ML infrastructure. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
