Staff Machine Learning Engineer in London

Staff Machine Learning Engineer in London

London Full-Time 80000 - 100000 £ / year (est.) No working from home possible

At a Glance

  • Tasks: Lead the development of cutting-edge ML infrastructure and drive AI innovation.
  • Company: Join Just Eat Takeaway.com, a global leader in online delivery.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Dynamic team environment with a commitment to diversity and inclusion.
  • Why this job: Shape the future of AI while making a real impact on millions of customers.
  • Qualifications: Experience in ML platforms, strong collaboration skills, and a passion for mentoring.

The predicted salary is between 80000 - 100000 £ per year.

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: The AI Growth team builds the AI systems that make Just Eat Takeaway.com'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 at scale. As 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 SageMaker, 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 Takeaway.com. 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.

Staff Machine Learning Engineer in London employer: 慨正橡扯

At 慨正橡扯, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the field of Behavioral Economics and Retirement Research. Our hybrid working model not only offers flexibility but also nurtures a vibrant work culture where employees are encouraged to grow and develop their skills through meaningful projects and leadership opportunities. Join us in Europe, where your expertise will directly contribute to enhancing investor outcomes and shaping impactful business strategies.

Contact Details:

慨正橡扯 Recruitment Team

We think you need these skills to ace Staff Machine Learning Engineer in London

Technical Leadership
Machine Learning Infrastructure
GPU Compute Strategy
Generative AI
Large Language Models (LLMs)
Model Serving Architectures
Kubernetes