Senior Machine Learning Engineer - AI

Position: Senior Machine Learning Engineer - Logistics
Logistics
Reporting to: Data Science Manager
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
Then Just Eat Takeaway.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.
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.
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.
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
Providing technical leadership and helping to shape best practices across the organisation
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
Working closely with Data Science teams to ensure seamless model deployment and continuous improvement
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
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
Strong problem-solving abilities and a proactive approach to identifying and implementing long-term solutions
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.
It's a competition for something incredibly valuable – our customers' choice. They guide every interaction, every decision, every innovation. Fun, fast-paced and supportive, the JET culture is about movement, growth, helping one another to succeed and celebrating wins. By truly living our values and embodying our behaviours, we’re building a customer-first culture which enables us to stay one step ahead of the competition.
Inclusion, Diversity & Belonging
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.