Just Eat Takeaway.com

Machine learning engineer in food delivery

In short

Senior Machine Learning Engineer role at a global online food delivery platform, leading end-to-end ML system design for algorithmic recommendations, from data pipelines to production inference and monitoring. The team works at the intersection of Data Science, Product and Backend Engineering, driving MLOps adoption and mentoring peers. Requires strong Python, production ML experience (not just notebooks), orchestration tools, cloud ML platforms, Terraform and Docker/Kubernetes knowledge. Hybrid role based in London.

About
Just Eat Takeaway.com is a leading global online food delivery platform. 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. We are looking for a Senior Machine Learning Engineer to join a cross functional team, focussing on growing our product algorithmic recommendations within Just Eat Takeaway.com.
Responsibilities
•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 organizations to ensure ML systems integrate seamlessly with the wider platform
•Lead projects, mentor peers, and advocate for engineering excellence within the data science domain
Requirements
•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
What we offer
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.

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