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Revolut is a global financial super app serving 80+ million customers with products spanning spending, saving, investing, exchanging, and travel. The company operates with 13,000+ employees across offices and remote locations worldwide.
The Technology team builds the systems and infrastructure powering Revolut's innovative platform. You will join the AI team as a Python Engineer focused on developing core MLOps infrastructure that enables scientists and engineers to solve complex challenges at scale.
In this role, you will:
- Design, build, and maintain scalable backend services and tooling supporting the AI lifecycle and GPU-based workloads
- Profile and optimize model training and inference workloads (latency, throughput, stability) using PyTorch and CUDA-enabled libraries
- Improve GPU compute utilization, memory consumption, and bandwidth across shared, multi-tenant, and multi-node environments
- Implement mixed-precision execution, quantization, efficient batching, gradient accumulation, and memory-efficient attention mechanisms
- Create repeatable benchmarking practices and automated regression tests to guide engineering teams in selecting execution frameworks and GPU types
- Write high-quality code and build automated solutions for heavily regulated financial systems
Requirements:
- Proven track record designing and operating scalable backend systems in production (Linux, Kubernetes, containerized workloads) using Python
- Experience running, profiling, and optimizing machine learning workloads built with PyTorch or equivalent on NVIDIA GPUs
- Solid understanding of GPU execution concepts: memory hierarchy, CPU/GPU synchronization, host-to-device transfers, CUDA stream behavior
- Familiarity with multi-GPU communication (NCCL), data/tensor parallelism, and resource allocation in Kubernetes
- Degree in STEM subject (or equivalent) with strong foundation in computer science principles, testing, observability, and operational ownership
