ML Infrastructure Engineer

ML Infrastructure Engineer at Nebius - Remote Nebius Nebius enables B2B companies to build local hyperscaling cloud platforms with cost-effective GPUs, InfiniBand network, and 50% less compute cost. They offer managed Kubernetes and a launch-ready business model for innovative cloud solutions. Internet Software & Services Information Technology 51-250 (120) 158 open positions Tags E-commerce Computer Programming Software Professional Services Computers Information Technology & Services B2C B2B Links ML Infrastructure Engineer 2 months ago Europe, United States Senior DevOps and Infrastructure Nebius Nebius enables B2B companies to build local hyperscaling cloud platforms with cost-effective GPUs, InfiniBand network, and 50% less compute cost. They offer managed Kubernetes and a launch-ready business model for innovative cloud solutions. Internet Software & Services 51-250 LinkedIn View All Jobs 158 Description - Work with hardware and development teams to profile and analyze GPU performance at the system and kernel level. - Evaluate and compare GPU performance across different platforms, architectures, and software stacks such as CUDA and ROCm. - Debug and optimize ML workloads to run efficiently on GPU hardware by identifying and resolving performance bottlenecks. - Perform acceptance testing for new GPU clusters to verify performance, stability, and compatibility for AI workloads. - Run experiments across diverse GPU system configurations to assess the impact of interconnect strategies and system-level optimizations. - Develop tools and dashboards to visualize performance metrics, bottlenecks, and trends. - Contribute to internal tooling, frameworks, and best practices for GPU benchmarking and optimization. Requirements - A strong understanding of the theoretical foundations of machine learning. - Deep understanding of performance aspects of large neural network training and inference, including data, tensor, contex