Senior Machine Learning Engineer

Just Eat Holding; Amsterdam; Hybrid; GBP 110,000 - 150,000; Full time

Job summary

Just Eat Takeaway.com is seeking a Senior Machine Learning Engineer for Logistics. You will drive development of scalable ML systems, ensuring deployment and production efficiency across real-time and batch inference environments.

You will lead with data science, collaborate with cross-functional teams, and champion best practices in ML engineering to deliver measurable impact on logistics operations.

Qualifications

• Expertise in cloud technologies (AWS) and container orchestration (Kubernetes).
• Production-grade ML systems deployment and MLOps practices.

Responsibilities

• Architect and oversee ML pipelines for logistics domains.
• Deploy and optimise ML models for real-time and batch inference.
• Collaborate with Data Science and cross-functional teams.

Skills

AWS

Kubernetes

DevOps

MLOps

MLflow

Airflow

Dagster

Kafka

Python

SQL

Communication

Leadership

Data Eng

Tools

Docker

Job description

Position: Senior Machine Learning Engineer - Logistics

Department: Logistics

Reporting to: Data Science Manager

Location: Amsterdam, London, UK, Berlin

Hybrid role: 3 days a week from our office & 2 days working from home

Full time / Part time role: Full time

Expected hours of work: Monday - Friday 37.5 hours

Ready for a challenge?

Then Just Eat Takeaway.com might be the place for you. We're a leading global online 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

As a Senior ML Engineer within the Logistics domain, you will drive the development of cutting-edge solutions that enhance the performance, scalability, and reliability of our machine learning systems. Working in close collaboration with the Data Science team, you will ensure that models are deployed seamlessly, optimised for production environments, and meet the highest standards of efficiency and accuracy at scale.

You will be responsible for managing both real-time and batch inference systems that are integral to our predictive platforms. Working closely with cross-functional teams, you will anticipate future needs, recommending and implementing long-term solutions that align with our business objectives. Beyond technical execution, you will communicate effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights.

This role offers the opportunity to provide technical leadership and help shape best practices across the organisation, ensuring our machine learning frameworks remain at the cutting edge of technological advancements while delivering measurable value to our logistics operations.

These are some of the key components to the position

• Architecting and overseeing the development of complex machine learning pipelines for relevant logistics sub-domains
• Implementing and launching Data Science applications with constant improvements using performant and efficient ML models
• Managing both real-time and batch inference systems that are integral to our predictive platforms
• Providing technical leadership and helping to shape best practices across the organisation
• Leading the integration of new technologies and tools into our infrastructure, staying ahead of industry trends
• Ensuring machine learning frameworks remain at the cutting edge of technological advancements
• Collaborating with cross-functional teams to anticipate future needs and recommend long-term solutions that align with business objectives
• Communicating effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights
• Optimising models for production environments to meet the highest standards of efficiency and accuracy at scale
• Working closely with Data Science teams to ensure seamless model deployment and continuous improvement

What will you bring to the team?

• Expert-level proficiency with cloud technologies (ideally AWS) and extensive experience with containerisation and orchestration (preferably Kubernetes)
• Deep understanding of software development, DevOps, and MLOps best practices, with a proven track record of applying them in production
• Extensive experience in designing, deploying, and maintaining scalable models and services in production environments
• Strong understanding of Machine Learning, with the ability to collaborate deeply with Data Scientists on model deployment and optimisation
• Experience with MLflow for experiment tracking and model management, and Airflow or Dagster for orchestrating end-to-end ML pipelines and workflows
• Significant experience with Data Engineering, Kafka, and stream processing technologies
• Proficiency in Python and SQL; experience with additional programming languages is a strong plus
• Excellent communication skills with the ability to work effectively across technical and non-technical teams
• Proven track record of technical leadership and driving best practices in engineering teams
• Strong problem-solving abilities and a proactive approach to identifying and implementing long-term solutions

At JET, this is how we play

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.

Being the best at what we do isn’t just about delivering on our strategy. It’s a competition for something incredibly valuable - our customers’ choice. Every time a customer decides where to order, they’re picking a side.

At the heart of the JET Customer League are our values and behaviours. They guide every interaction, every decision, every innovation. These are the actions we need to perform consistently and brilliantly, to surpass the competit