At a Glance
- Tasks: Lead the design and implementation of machine learning systems to enhance our food delivery platform.
- Company: Join Just Eat Takeaway.com, a global leader in online food delivery.
- Benefits: Hybrid work model, competitive salary, and a vibrant team culture.
- Why this job: Make a real impact on millions of customers with innovative tech solutions.
- Qualifications: Strong Python skills and experience in production ML systems required.
- Other info: Dynamic environment with a focus on inclusion, diversity, and personal growth.
The predicted salary is between 48000 - 72000 £ per year.
Ready for a challenge? Just Eat Takeaway.com might be the place for you. We're a leading global online food delivery platform, and our vision is to empower everyday convenience. Whether it's a Friday-night feast, a post-gym poke bowl, or grabbing some groceries, our tech platform connects tens of millions of customers with hundreds of thousands of restaurant, grocery and convenience partners across the globe.
About this role: We are looking for a Senior Machine Learning Engineer to join a cross-functional team, focusing on growing our product algorithmic recommendations within Just Eat Takeaway.com. Your team will focus on evolving existing machine learning and AI capabilities across the platform, improving those capabilities, and innovating new ones for the future. As a Senior Engineer, you will drive our architecture, write highly scalable and testable code, mentor engineers and challenge our teams to strive for excellence. You will work closely with a large number of teams, both internal and external, with inner-sourced development as our standard way of working. Ownership is one of the core engineering principles in our organisation - we write it and we own it. Engineers are expected to take responsibility for their work from discovery to production, ensuring the ongoing reliability and stability of our systems.
Location: Hybrid - 3 days a week from our office & 2 days working from home
Reporting to: Technology Manager
These are some of the key ingredients to the role:
- Collaborate extensively with Data Scientists, Product Managers, and Backend Engineers to bridge the gap between model development and production systems.
- Lead the architectural design of end-to-end ML systems, from data ingestion and training pipelines to real-time inference and monitoring infrastructure.
- Transform innovative data science prototypes into robust, scalable, and secure production software, taking ownership of the "path to production."
- Drive the adoption of MLOps best practices (CI/CD for ML, model versioning, feature stores) to accelerate the feedback loop for Data Scientists.
- Effectively communicate the complexities of ML systems (e.g., latency vs. accuracy trade-offs) to technical and non-technical stakeholders.
- Build and maintain a strong network across the Data and Engineering organisations to ensure ML systems integrate seamlessly with the wider platform.
- Lead projects, mentor peers, and advocate for engineering excellence within the data science domain.
What will you bring to the table?
- Proficiency in Python and a strong understanding of software engineering principles (OO design, patterns, testing) applied to Machine Learning.
- Demonstrable experience designing and operating ML systems in production (not just training models in notebooks), including familiarity with serving patterns (e.g., REST APIs, batch inference, event-driven).
- Experience with orchestration tools (e.g., Airflow, Dagster) and cloud-native ML platforms (e.g., AWS SageMaker, GCP Vertex AI).
- Ability to influence decision-making regarding infrastructure and tooling, balancing "build vs. buy" discussions.
- Strong knowledge of Infrastructure as Code (Terraform) and containerization (Docker/Kubernetes).
- Familiarity with data engineering fundamentals (SQL, distributed data processing) to debug and optimize data flows.
- A proactive mindset to automate manual processes and a passion for improving the developer experience for Data Scientists.
At JET, this is on the menu: Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment. Fun, fast-paced and supportive, the JET culture is about movement, growth and about celebrating every aspect of our JETers. Thanks to them we stay one step ahead of the competition.
Inclusion, Diversity & Belonging: No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat Takeaway.com. We're committed to creating an inclusive culture, encouraging diversity of people and thinking, in which all employees feel they truly belong and can bring their most colourful selves to work every day.
What else is cooking? Want to know more about our JETers, culture or company? Have a look at our career site where you can find people's stories, blogs, podcasts and more JET morsels.
Senior Machine Learning Engineer in London employer: Just Eat Takeaway.com
Contact Detail:
Just Eat Takeaway.com Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Just Eat Takeaway.com on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your machine learning projects. When you get that interview, having tangible examples of your work will set you apart from the crowd.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your Python and ML concepts. Use platforms like LeetCode or HackerRank to sharpen your coding skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Just Eat Takeaway.com family.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior Machine Learning Engineer role. Highlight your experience with ML systems in production and any relevant projects that showcase your skills in Python and software engineering principles.
Showcase Your Collaboration Skills: Since this role involves working closely with Data Scientists, Product Managers, and Backend Engineers, be sure to mention any past experiences where you successfully collaborated across teams. We love seeing how you bridge gaps and drive projects forward!
Demonstrate Ownership: At Just Eat Takeaway.com, we value ownership. In your application, share examples of how you've taken responsibility for your work from discovery to production. This could be a project where you led the architectural design or implemented MLOps best practices.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to see your application and get to know you better. Plus, it shows you're keen on joining our team at Just Eat Takeaway.com!
How to prepare for a job interview at Just Eat Takeaway.com
✨Know Your ML Systems Inside Out
Make sure you can discuss your experience with designing and operating machine learning systems in production. Be ready to explain the intricacies of serving patterns, like REST APIs and batch inference, as well as how you've tackled latency vs. accuracy trade-offs.
✨Show Off Your Collaboration Skills
Since this role involves working closely with Data Scientists, Product Managers, and Backend Engineers, prepare examples of how you've successfully collaborated in cross-functional teams. Highlight any projects where you bridged gaps between model development and production systems.
✨Demonstrate Your Proficiency in Python
Brush up on your Python skills and be prepared to discuss how you've applied software engineering principles to machine learning. You might even want to share specific examples of scalable and testable code you've written in past projects.
✨Emphasise Your MLOps Knowledge
Familiarise yourself with MLOps best practices, such as CI/CD for ML and model versioning. Be ready to discuss how you've implemented these practices in previous roles to improve the feedback loop for Data Scientists and enhance overall system reliability.