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- Tasks: Lead a team to innovate product engagement using advanced machine learning models.
- Company: A leading digital marketplace with a focus on innovation and technology.
- Benefits: Salary up to £140,000, flexible working, and a progressive benefits package.
- Why this job: Make a real impact in the eCommerce space with cutting-edge ML technology.
- Qualifications: 7+ years in machine learning and leadership experience required.
- Other info: Remote/hybrid work options available for a better work-life balance.
The predicted salary is between 84000 - 140000 £ per year.
A leading digital marketplace is seeking an experienced Engineering Manager focused on machine learning to lead their recommendation team. This role involves driving innovation in product engagement through advanced ML models.
Candidates should have over 7 years of experience in machine learning, particularly in search and recommendation systems, along with leadership experience.
Offering a salary up to £140,000 and a progressive benefits package, this role supports flexible working arrangements including remote work.
ML Engineering Manager Marketplace/Ecommerce (Remote/Hybrid) in Bury employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineering Manager Marketplace/Ecommerce (Remote/Hybrid) in Bury
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in ML or at the company you're eyeing. A friendly chat can open doors and give you insider info that could set you apart.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies showcasing your past projects in machine learning, particularly around recommendation systems. This will help us see your hands-on experience and innovative thinking.
✨Tip Number 3
Ace the interview by practising common questions related to ML engineering and leadership. We recommend doing mock interviews with friends or using online platforms to get comfortable with articulating your thoughts.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace ML Engineering Manager Marketplace/Ecommerce (Remote/Hybrid) in Bury
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and leadership. We want to see how your background aligns with the role, especially in search and recommendation systems.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about ML and how you can drive innovation in product engagement. Let us know what excites you about this opportunity.
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Share specific examples of ML models you've developed or led, particularly those that improved product engagement. We love seeing real-world applications of your skills.
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 this exciting role. Don’t miss out!
How to prepare for a job interview at Jobster
✨Know Your ML Models Inside Out
Make sure you brush up on the latest advancements in machine learning, especially in recommendation systems. Be ready to discuss specific models you've worked with and how they impacted product engagement.
✨Showcase Your Leadership Skills
Prepare examples of how you've led teams in the past. Highlight your approach to mentoring and driving innovation within your team, as this role requires strong leadership in a technical environment.
✨Understand the Company’s Marketplace
Research the digital marketplace thoroughly. Familiarise yourself with their products, target audience, and any recent innovations they've introduced. This will help you tailor your answers and show genuine interest.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions. Brush up on algorithms, data structures, and system design related to ML. Practising coding problems or case studies can also give you an edge during the interview.
