# Staff ML Performance Engineer \(Training Efficiency\) - Company: [Wayve]() - Location: Sunnyvale, California USA - Team: AI Platform - Employment type: Full Time - Posted: February 26, 2026 ## Job description ## **The role** We are looking for a Staff ML Performance Engineer to join our Training Tech team working on optimizing large scale ML jobs to enable scaling our models to the next order of magnitude. A successful candidate will increase efficiency of training and inference workloads in order to allow Wayve to train larger models faster. Key responsibilities: * Profile ML workloads to identify their bottlenecks, e.g. using NVIDIA Nsight Systems * Design and implement efficiency improvements to maximize MFU and throughput, e.g. parallelism, model compilation, mixed precision * Design and implement observability tools to identify bottlenecks and drive performance improvements, e.g. to track MFU, throughput, latency, etc * Design and implement benchmarking tools, e.g. to track efficiency gains or regressions * Collaborate closely with Research teams to integrate training efficiency improvements and create a culture of performance optimization ## **About you** In order to set you up for success in this role, we’re looking for the following skills and experience. **Essential** * 10+ years of industry experience driving performance engineering across ML systems, GPU compute infrastructure, distributed platforms or similar field. * Experience optimizing large scale jobs on GPU compute clusters. * Experience in working in platform teams and working with research teams. * Experience in writing, reporting, and tracking performance benchmarks in an open and accessible way. * Ability to write high quality, well-structured and tested Python code * BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience **Desirable** * Experience working with concurrent, parallel and distributed computing. * Experience using NVIDIA NSight Systems or other system profilers. * Experience implementing GPU kernels (CUDA, Triton, etc). * Knowledge of computing fundamentals - what makes code fast, secure and reliable. This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably estimated salary for this role ranges from $336,400 to $359,000, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience. #LI-HH1 ## Apply [Apply on Wayve]() Canonical job page: