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- Tasks: Build and scale machine learning infrastructure for smart cameras.
- Company: Leading sports technology company in the UK with a focus on innovation.
- Benefits: Competitive salary ranging from £64,000 to £111,000 based on experience.
- Why this job: Join a dynamic team and drive automation in cutting-edge AI projects.
- Qualifications: Strong background in production MLOps and infrastructure code.
- Other info: Collaborative environment with opportunities for professional growth.
The predicted salary is between 64000 - 111000 £ per year.
A leading sports technology company in the United Kingdom is looking for a Senior MLOps Engineer to build and scale machine learning infrastructure for smart cameras. This role involves designing scalable systems, collaborating with diverse teams, and driving automation for model deployment.
The ideal candidate has a robust background in production MLOps, technical expertise in infrastructure code, and a problem-solving mindset.
Compensation ranges from £64,000 to £111,000 annually, based on experience and skills.
Senior MLOps Engineer — Edge AI & Fleet Deployment employer: Hudl
Contact Detail:
Hudl Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLOps Engineer — Edge AI & Fleet Deployment
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially those involving scalable 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 technical questions related to infrastructure code and model deployment. Practice explaining your thought process clearly, as collaboration is key in this role.
✨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, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior MLOps Engineer — Edge AI & Fleet Deployment
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in MLOps and infrastructure code. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about building scalable systems and how you can contribute to our team. Keep it engaging and personal – we love to see your personality!
Showcase Problem-Solving Skills: In your application, give examples of how you've tackled challenges in previous roles. We’re looking for that problem-solving mindset, so share specific instances where you’ve driven automation or improved processes.
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 a few clicks and you’re done!
How to prepare for a job interview at Hudl
✨Know Your MLOps Inside Out
Make sure you brush up on your MLOps knowledge, especially around building and scaling machine learning infrastructure. Be ready to discuss specific tools and frameworks you've used in production, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Collaboration Skills
Since this role involves working with diverse teams, prepare examples of how you've successfully collaborated in the past. Think about cross-functional projects where you contributed to design or deployment, and be ready to explain your role and impact.
✨Demonstrate Your Problem-Solving Mindset
Be prepared to tackle hypothetical scenarios during the interview. Practice articulating your thought process when faced with a technical problem, especially in the context of automation for model deployment. This will show your analytical skills and ability to think on your feet.
✨Research the Company and Its Technology
Familiarise yourself with the company's products and technology, particularly their smart cameras and how they leverage AI. This will not only help you tailor your answers but also demonstrate your genuine interest in the role and the company.
