Key Notes
At least eight years’ software engineering, including three years leading or architecting data projects, are required for this Wayve staff role. You’ll set ingestion-system direction and unify fleet and partner data for AI research across petabyte-scale pipelines. A relevant technical degree and DAG-orchestration expertise are required, with mentoring and distributed-processing capability. The full-time London role is hybrid; robotics sensor data and governance frameworks are desirable experience.
What You'll Work On
- Define the ingestion-pipeline roadmap and architecture, leading features that normalise and distribute internal and external data for AI training and research.
- Improve data-pipeline interfaces and processing reliability, reducing bottlenecks and latency and strengthening recovery and service-level performance across petabyte workloads.
- Set observability, monitoring and alerting practices, coordinating robotics, ML, research and data-governance teams around scalable ingestion systems.
- Mentor ingestion engineers and support hiring and onboarding, establishing technical standards and shared ownership across the data-pipeline organisation.
What They Are Looking For
- Experience: At least eight years developing and operating complex scalable pipelines, including three years leading or architecting data-engineering projects.
- Technical: DAG orchestration such as Airflow, Flyte or Ray, distributed processing and pipeline optimisation.
- Experience: Technical pipeline leadership and a track record of mentoring and developing engineers.
- Qualification: A bachelor’s degree or higher in computing, engineering or a related technical field.
- Stakeholder: Clear collaboration across interdisciplinary data, research and engineering teams.
- Preferred: Robotics sensor pipelines, third-party datasets, GDPR, TISAX, ASPICE or integrated observability are desirable.