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- Tasks: Lead a team to develop and scale machine learning systems for millions of users.
- Company: A leading digital marketplace focused on innovation and growth.
- Benefits: Competitive salary up to £140,000, flexible working, and wellbeing support.
- Why this job: Make a significant impact in the world of machine learning and lead a talented team.
- Qualifications: Experience in applied machine learning, cloud platforms, and strong leadership skills.
- Other info: Join a dynamic environment with a focus on personal development and career growth.
The predicted salary is between 84000 - 196000 £ per year.
A leading digital marketplace is seeking an experienced Engineering Manager for their MLOps function. This high-impact role involves leading a team of engineers to develop and scale machine learning systems. The ideal candidate will have experience in applied machine learning, cloud platforms, and a strong leadership background.
The company offers a competitive salary of up to £140,000 plus benefits, flexible working arrangements, and a focus on wellbeing and development.
Remote MLOps Engineering Manager - Scale ML for 35M Users in Bolton employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote MLOps Engineering Manager - Scale ML for 35M Users in Bolton
✨Tip Number 1
Network like a pro! Reach out to folks in the MLOps space on LinkedIn or at industry events. A personal connection can make all the difference when it comes to landing that dream role.
✨Tip Number 2
Showcase your skills! Create a portfolio or GitHub repository with your machine learning projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your leadership and technical skills. Be ready to discuss how you've scaled ML systems in the past and how you can lead a team effectively.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes give you an edge. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Remote MLOps Engineering Manager - Scale ML for 35M Users in Bolton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in applied machine learning and cloud platforms. We want to see how your skills align with the role, so don’t be shy about showcasing your leadership background!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about MLOps and how you can help us scale our systems for 35 million users. Keep it engaging and personal.
Showcase Relevant Projects: If you've worked on any projects that demonstrate your MLOps expertise, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
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 Jobster
✨Know Your MLOps Inside Out
Make sure you brush up on your knowledge of MLOps principles and practices. Be ready to discuss how you've applied machine learning in real-world scenarios, especially in scaling systems for large user bases. This will show that you understand the challenges and can lead a team effectively.
✨Showcase Your Leadership Skills
Prepare examples of how you've successfully led teams in the past. Think about specific situations where you motivated your team, resolved conflicts, or drove projects to completion. This will demonstrate your capability as an Engineering Manager and your fit for the role.
✨Familiarise Yourself with Cloud Platforms
Since the role involves cloud platforms, make sure you're up to speed with the ones relevant to the company. Be ready to discuss your experience with services like AWS, Azure, or Google Cloud, and how you've leveraged them in your previous roles to enhance machine learning operations.
✨Emphasise Wellbeing and Development
The company values wellbeing and development, so be prepared to talk about how you prioritise these aspects within your team. Share your thoughts on fostering a positive work environment and how you encourage continuous learning and growth among your engineers.
