Hiring.Camp

Staff Machine Learning Engineer

Takeaway

·

3 days ago

Location
Fleet Place Office, United Kingdom · Amsterdam Office
Workplace
Hybrid
Type
Full-time
Department
Engineering
Seniority
Senior
Source
Workday

Description

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 JustEatTakeaway.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.

At JET, this is how we play 

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. 

Being the best at what we do isn’t just about delivering on our strategy. It's a competition for something incredibly valuable – our customers' choice. Every time a customer decides where to order, they're picking a side. 

At the heart of the JET Customer League are our values and behaviours. They guide every interaction, every decision, every innovation. These are the actions we need to perform consistently and brilliantly, to surpass the competition and earn our customers’ loyalty, again and again.  

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 

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. 

What else are we delivering?

Want to know more about our JETers, culture or company? Have a look at our career site where you can find people's stories, blogs, podcasts and more JET journeys.
 

Are you ready to join the team? Apply now!

#LI-MM2

Skills

AWSGCPKubernetesMachine Learning

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