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- Tasks: Lead teams to optimise delivery logistics using machine learning systems.
- Company: Top food delivery company focused on innovation and quality.
- Benefits: Competitive salary, comprehensive benefits, and support for employee wellbeing.
- Why this job: Make a real impact on food delivery speed and quality with cutting-edge technology.
- Qualifications: Experience in managing ML engineers and deploying systems in production.
- Other info: Join a dynamic team with opportunities for growth in a fast-paced environment.
The predicted salary is between 43200 - 72000 £ per year.
A leading food delivery company is seeking a Machine Learning Engineering Manager to lead teams focused on optimising delivery logistics. This role involves owning machine learning systems that enhance food quality and delivery speed, working closely with cross-functional teams.
Candidates should have experience managing machine learning engineers and deploying systems into production, with a strong background in logistics and optimisation.
The position offers a competitive salary and comprehensive benefits designed to support employee wellbeing.
Lead ML Engineering for Real-Time Delivery employer: Deliveroo
Contact Detail:
Deliveroo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead ML Engineering for Real-Time Delivery
✨Tip Number 1
Network like a pro! Reach out to folks in the food delivery and logistics space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your past projects in machine learning and logistics optimisation. Real-world examples speak volumes.
✨Tip Number 3
Ace the interview! Research common questions for ML Engineering Managers and practice your responses. We want you to shine and show how you can lead teams effectively.
✨Tip Number 4
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.
We think you need these skills to ace Lead ML Engineering for Real-Time Delivery
Some tips for your application 🫡
Show Your Passion for Machine Learning: When writing your application, let us see your enthusiasm for machine learning and how it can transform delivery logistics. Share specific examples of projects you've worked on that relate to optimising processes or enhancing quality.
Highlight Your Leadership Experience: We want to know about your experience managing teams! Make sure to detail your leadership style and how you've successfully guided machine learning engineers in the past. This will help us understand how you can lead our teams effectively.
Tailor Your Application to Us: Don’t just send a generic application! Take the time to tailor your CV and cover letter to our company and the role. Mention how your skills align with our mission to enhance food delivery through innovative machine learning solutions.
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 shows us you’re serious about joining our team!
How to prepare for a job interview at Deliveroo
✨Know Your ML Stuff
Brush up on your machine learning concepts, especially those related to logistics and optimisation. Be ready to discuss specific algorithms you've used in past projects and how they improved delivery systems.
✨Showcase Leadership Skills
Prepare examples of how you've successfully managed teams of machine learning engineers. Highlight your approach to mentoring and guiding your team through challenges, as this role requires strong leadership.
✨Understand the Business
Familiarise yourself with the food delivery industry and the company's specific challenges. Being able to discuss how machine learning can solve real-world problems in delivery logistics will set you apart.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's current machine learning initiatives and future goals. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
