Data Scientist (NLP Deep Learning Engineer)

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 75+ 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™. We have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. We're looking for brilliant 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 Data Science team solves complex problems with smart, practical solutions and improves how customers experience Revolut. Our Deep Learning Engineers are at the forefront of GenAI and LLM integration, building transformative products that range from user-facing tools to advanced process optimisation.

We're looking for a Deep Learning Engineer to work with the most advanced LLMs available, developing solutions that have a tangible impact on millions of customers worldwide.

You'll collaborate cross-functionally with Product Owners, Software Engineers, Data Analysts, and Operations Managers to deliver automated, scalable solutions that elevate and revolutionise customer interaction.

Responsibilities

• Building AI-driven features from scratch, like personal assistants, chatbots, copilots, and more
• Developing user-focused and backend features using deep learning
• Delivering impactful, scalable, data-driven AI solutions
• Collaborating with Product, Engineering, and Data teams to solve deep learning challenges
• Integrating cutting-edge AI technologies to drive innovation at Revolut

Requirements

• Experience in deep learning within natural language processing area and large language models
• A bachelor's degree in a STEM major (mathematics, computer science, engineering)
• Excellent knowledge of data science (Python, SQL) and production tools
• A deep understanding of probability and statistics fundamentals
• Big-picture thinking to correctly diagnose problems and productionise research
• Excellent communication and collaboration skills to partner with Product Owners and business heads

Nice to Have

• A master's or PhD in a quantitative discipline
• Solid experience with additional programming languages, such as Java, Scala, C++
• Experience at a large tech company worth >$15B
• School/university Olympic medal competitions in physics, maths, economics, or programming