About Revolut
People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 70+ million customers get more from their money every day.

As we continue our lightning-fast growth,‌ 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work™. So far, we have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.

About the role
Our Technology team builds the systems and experiences that keep Revolut moving. From the infrastructure behind our innovative app to the features used by millions of people around the world, they bring sharp thinking, speed, and a focus on meaningful impact to everything they do.

We’re looking for an AI Platform Engineer to build the infrastructure behind our ML ecosystem. You'll enable scalable model training, optimising them efficiently across multi-cloud environments, and develop AI platform capabilities across Revolut.

Up to shape what’s next in finance? Let’s get in touch.

What you'll be doing* Solving infrastructure and architectural challenges at scale

• Building and scaling multi-cloud ML infrastructure platforms (GCP, Nebius, selected vendors)
• Owning infrastructure, observability, reliability, and scalability end to end
• Acting as mentors and multipliers in coding, system design, and SDLC quality
• Unblocking teams, domains, and processes through expertise and foundational contributions
• Supporting internal AI platforms across training, inference, and model infrastructure
• Optimising GPU usage, capacity planning, reservations, and workload placement strategies

What you'll need* A background in high-throughput, scalable distributed systems

• Impressive coding skills and confidence working with Python-based platforms
• Platform, infrastructure, or internal tooling engineering experience
• Experience with GPU infrastructure, workload orchestration, or ML platform environments