> Markdown version of [/jobs/ext/3793034-senior-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/3793034-senior-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Machine Learning Engineer

- **Company:** Just Eat Takeaway.com
- **Location:** Epping, UK (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Cloud Engineering, Continuous Integration, Information Engineering, Software Debugging, Distributed Computing Environment, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Azure Machine Learning, Software Engineering, SQL Databases, Data Streaming, Workflow Management Systems, Feature Store, Data Ingestion, Google Vertex AI, Backend, Containerization, Kubernetes, Real-time Inference, Machine Learning Operations, Restful APIs, Terraform, Software Version Control, Docker
- **Published:** October 17, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/senior-machine-learning-engineer/52124742

## About the Role

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

## Description

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.
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 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.
This role offers you the opportunity to lead, deliver, and care for cutting-edge ML systems that impact millions of customers daily.

These are some of the key components to the position:
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