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Machine Learning Engineer

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: 慨正橡扯
Full Time position
Listed on 2026-07-20
Job specializations:
  • Software Development
    Software Architect, Cloud Engineer - Software, AI Engineer (Applied/Software), DevOps
Salary/Wage Range or Industry Benchmark: 120000 - 180000 GBP Yearly GBP 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Position: Staff Machine Learning Engineer
Location: Greater London

Ready for a challenge?

Then Just Eat  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

The AI Growth team builds the AI systems that make 's marketplace more relevant for millions of customers and partners across 14 countries. From powering personalised recommendations and intelligent targeting to developing our foundation model platform, we’re shaping the future of AI  a Staff Machine Learning Engineer, you’ll provide technical leadership for the ML infrastructure that underpins these capabilities, working across teams to define the architecture, roadmap and engineering direction for the next generation of our platform.

You’ll play a key role in helping us live our values of Lead, Deliver and Care, combining strategic thinking with hands‑on technical leadership. Working closely with engineers, data scientists and platform teams, you’ll make decisions that enable innovation at scale while balancing performance, cost and reliability to deliver the best possible experience for our customers.

These are some of the key components to the position
  • Own the technical roadmap for the ML infrastructure domain, defining priorities across GPU compute, model serving, training platforms and observability.
  • Lead the evolution of our foundation model platform as we expand from a GCP‑first environment to a hybrid AWS and GCP architecture.
  • Define GPU compute strategy across Kubernetes, Vertex AI and Sage Maker, balancing performance, scalability and cost efficiency.
  • Drive the production adoption of Generative AI and LLM capabilities, establishing best practices for evaluation, deployment, experimentation and governance.
  • Collaborate with engineering teams to resolve cross‑platform dependencies and remove technical blockers before they impact delivery.
  • Provide technical leadership and architectural guidance across multiple teams, influencing engineering direction beyond your immediate domain.
  • Partner with product, platform and infrastructure teams to ensure ML systems are reliable, scalable and aligned to business priorities.
  • Raise the bar by improving platform observability, monitoring model performance, training efficiency and operational health across the ML ecosystem.
  • Mentor engineers and promote engineering excellence through knowledge sharing, technical reviews and collaborative problem solving.
  • Own architectural decisions that balance speed, scalability and long‑term maintainability while supporting Just Eat's AI growth strategy.
What will you bring to the team?
  • Experience defining and delivering technical roadmaps for large‑scale ML platforms, aligning engineering priorities with business goals.
  • Strong understanding of production ML architecture, balancing latency, model quality, infrastructure cost and maintainability.
  • Experience leading the adoption of LLMs or Generative AI from experimentation through to production deployment and operation.
  • Deep knowledge of model serving architectures, with the ability to evaluate online, batch, synchronous and asynchronous serving strategies.
  • Experience building or overseeing monitoring for multiple production ML models, including model drift, data quality and operational performance.
  • Advanced Kubernetes knowledge, with the ability to troubleshoot cluster‑level issues across security, networking, RBAC and platform operations.
  • Strong collaboration and stakeholder management skills, influencing technical decisions across multiple engineering teams and business functions.
  • Pragmatic problem‑solving mindset, balancing rapid delivery with long‑term platform scalability and engineering excellence.
  • Experience optimising GPU infrastructure, cloud platforms or distributed ML workloads to improve efficiency and reduce operational costs.
  • Passion for mentoring others, sharing knowledge and fostering a collaborative culture that helps teams deliver their best work.
Inclusion, Diversity & Belonging

No matter who you are, what you look like, who you love, or where you are from, you can find your place at Just Eat  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.

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