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Nebius
ML Infrastructure Engineer
Remote · Europe, USA · Full time · Mid level
About the role
Lead and support benchmarking of GPU platforms for machine learning and AI workloads. Evaluate GPU hardware performance to optimize platform and hardware development.
What you’ll do
• Profile and analyse GPU performance at system and kernel level. • Evaluate GPU performance across platforms and software stacks. • Debug and optimise ML workloads on GPU hardware. • Perform acceptance testing for new GPU clusters. • Develop tools and dashboards for performance metrics visualization.
What you’ll bring
• Profound understanding of machine learning theory. • Deep knowledge of neural network training and inference performance. • Experience with deep learning frameworks like PyTorch, JAX. • Good understanding of GPU stack: CUDA, NCCL, drivers. • Familiarity with containerized environments like Docker, Kubernetes.
Life at Nebius
Competitive compensation, career growth, flexibility, collaborative culture, impactful AI projects, international teams.
About Nebius
Nebius builds a full-stack AI cloud platform supporting developers and enterprises with AI/ML infrastructure. Listed on Nasdaq and headquartered in Amsterdam with global R&D hubs.