Machine Learning Engineer, Performance Tooling

Job description

About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The role You’ll join the AI Performance Tooling team within Wayve’s AI Performance organization, which makes model training and inference faster, more efficient, and more predictable across cloud and embedded hardware. Our mission is to enable data-driven AI performance decisions across priority workloads and hardware targets: Measure performance teams can trust; Monitor trends and catch regressions; Predict the cost of changes before we run them; Advise on bottlenecks and prioritized opportunities. You’ll build tools that reason across the AI stack — models and operators, compilers, runtimes, accelerators, and distributed training infrastructure — turning profiling data into a clear picture of where time, memory, power, and compute go, and what proposed changes will do to latency, throughput, compute spend, and capacity. You’ll work closely with model, compiler, runtime, platform, and hardware teams, bringing a cross-stack view that turns measurement into clear recommendations. Key responsibilities Design and build reliable, self-service performance tools that scale across models, hardware targets, and development workflows. Shape how Wayve measures and predicts AI performance, and set the standards other teams build on. Model theoretical peak for a platform, compare with achieved performance, and pinpoint where efficiency is lost at layer and op level. Predict latency, memory, utili…