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- Tasks: Lead engineering teams to deliver innovative Machine Learning and AI platforms.
- Company: A leading fitness tech company in Greater London with a focus on innovation.
- Benefits: Competitive salary, career growth opportunities, and a chance to shape AI solutions.
- Why this job: Make a real impact in the fitness industry through advanced technology.
- Qualifications: 8+ years in ML production, strong leadership skills, and cloud expertise.
- Other info: Join a dynamic team and drive growth with cutting-edge solutions.
The predicted salary is between 48000 - 72000 £ per year.
A leading fitness technology company in Greater London is seeking an experienced ML Engineering Manager. This role involves leading engineering teams in delivering cutting-edge Machine Learning and AI platforms.
Candidates must have 8+ years of experience in ML production implementation, proven people leadership skills, and expertise in cloud technologies, preferably GCP.
The position offers an opportunity to shape the AI backbone of the company and drive growth through advanced technological solutions.
ML Engineering Manager: Lead Production AI & MLOps employer: ON RUNNING
Contact Detail:
ON RUNNING Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineering Manager: Lead Production AI & MLOps
✨Tip Number 1
Network like a pro! Reach out to your connections in the fitness tech industry and let them know you're on the lookout for opportunities. A personal recommendation can go a long way in landing that ML Engineering Manager role.
✨Tip Number 2
Showcase your expertise! Prepare a portfolio or case studies that highlight your experience in ML production implementation and cloud technologies. This will help you stand out during interviews and demonstrate your hands-on skills.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or use online platforms to refine your answers, especially around leadership and technical challenges. We want you to feel confident when discussing your vision for AI and MLOps.
✨Tip Number 4
Apply through our website! We make it easy for you to find and apply for roles that match your skills. Plus, it shows your commitment to joining our team and helps us get to know you better right from the start.
We think you need these skills to ace ML Engineering Manager: Lead Production AI & MLOps
Some tips for your application 🫡
Showcase Your Experience: Make sure to highlight your 8+ years of experience in ML production implementation. We want to see how you've led teams and delivered successful projects, so don’t hold back on the details!
Demonstrate Leadership Skills: Since this role is all about leading engineering teams, share examples of how you've successfully managed people in the past. We love to see how you inspire and motivate your team to achieve great results.
Highlight Cloud Expertise: If you've got experience with cloud technologies, especially GCP, make it a focal point in your application. We’re keen to know how you’ve leveraged these tools to enhance ML and AI platforms.
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 our team!
How to prepare for a job interview at ON RUNNING
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and production implementation techniques. Be ready to discuss specific projects you've worked on, especially those involving GCP or similar cloud technologies. This will show that you not only understand the theory but also have practical experience.
✨Showcase Your Leadership Skills
As a potential ML Engineering Manager, it's crucial to demonstrate your people leadership skills. Prepare examples of how you've successfully led teams in the past, resolved conflicts, or mentored junior engineers. This will highlight your ability to manage and inspire a team effectively.
✨Understand the Company’s Vision
Research the fitness technology company and its current AI initiatives. Understanding their goals and challenges will allow you to tailor your responses and show how your expertise can help shape their AI backbone. It’s all about aligning your vision with theirs!
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and knowledge of MLOps. Practice explaining complex concepts in simple terms, as you may need to communicate these ideas to non-technical stakeholders. Being clear and concise will set you apart from other candidates.
