Staff Software Engineer, Data Enrichment Platform

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 As a Staff Software Engineer for the Data Enrichment Platform, you will own the technical vision for the systems that enable Wayve’s teams to deploy, run, evaluate and continually improve machine-learning models. You will shape a platform that processes petabytes of driving data, operates across large GPU fleets and supports dozens of model engineers. Working across model engineering, infrastructure, compute and data teams, you will create dependable, self-service capabilities that improve model quality while reducing cost and operational effort. Key responsibilities: Define the technical vision and architecture for Wayve’s end-to-end Data Enrichment Platform. Lead the development of backend services, APIs, model-execution workflows, versioned outputs, annotation capabilities and dataset catalogues. Build scalable and reliable systems for large-scale inference, automated evaluation, model monitoring, active learning and retraining. Partner with platform teams to address data locality, scheduling, capacity, backpressure, failure recovery, observability and cost across petabyte-scale datasets and large GPU fleets. Make effective build, buy, reuse, integrate, consolidate and replace decisions as Wayve’s requirements and the technology landscape evolve. Establish clear technical boundaries and working relationships across AI Platform, infrastructure, compute, storage, data and mo…