Staff ML Performance Engineer (Training Efficiency)

Join Wayve, a leading company in the self-driving car industry, as a Staff ML Performance Engineer. In this role, you will optimize large-scale ML jobs to enhance training efficiency and enable the scaling of our models. You will collaborate closely with research teams, design and implement efficiency improvements, and create a culture of performance optimization. Enjoy benefits such as private healthcare, paid time off, mental health resources, community and social events, competitive compensation, and learning and development opportunities.

• Profiling ML workloads to identify bottlenecks and implementing efficiency improvements.
• Designing and implementing observability and benchmarking tools to track performance.
• Collaborating closely with Research teams to integrate training efficiency improvements.
• Experience in writing, reporting, and tracking performance benchmarks in an open and accessible way
• 10+ years of industry experience driving performance engineering across ML systems, GPU compute infrastructure, distributed platforms or similar field
• BS or MS in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience
• Experience optimizing large scale jobs on GPU compute clusters
• Experience in working in platform teams and working with research teams
• Ability to write high quality, well-structured and tested Python code
• Experience working with concurrent, parallel and distributed computing
• Knowledge of computing fundamentals - what makes code fast, secure and reliable
• Experience implementing GPU kernels (CUDA, Triton, etc)
• Experience using NVIDIA NSight Systems or other system profilers
• We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply