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# Senior Machine Learning Engineer

- **Company:** Just Eat Takeaway.com
- **Location:** Chertsey, UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Cloud Computing, Information Engineering, DevOps, Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, SQL Databases, Containerization, Kubernetes, Apache Kafka, Machine Learning Operations, Stream Processing, Programming Languages
- **Published:** November 7, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/senior-machine-learning-engineer/55250337

## About the Role

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

## Description

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