Staff ML Performance Engineer, Performance Architecture

📋 Description

• Profiling ML workloads across training and cloud inference to identify bottlenecks, using system
• Designing and implementing efficiency improvements to maximise MFU, throughput and utilisation
• Building reusable, cross-target optimisations (kernels, data loaders, frameworks such as Triton)
• Designing and implementing benchmarking tools to track efficiency gains and catch regressions on
• Informing cloud GPU hardware strategy and readiness in partnership with platform teams
• Building a culture of performance optimisation with Research and model teams

🎯 Requirements

• 10+ years of industry experience driving performance engineering across ML systems, GPU compute
• Optimised large-scale workloads on GPU compute clusters, for training, inference or both
• Written, reported and tracked performance benchmarks in an open and accessible way
• High quality, well-structured and tested Python code
• BS or MS in Machine Learning, Computer Science, Engineering or a related technical discipline, or

🎁 Benefits

• Salaries benchmarked against the market annually
• Meaningful equity, sharing in the ownership and long term success of Wayve
• Relocation support and visa sponsorship where applicable
• Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
• Learning and development budgets with support for training, conferences and growth
• Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave