Lead Technical Program Manager Data
Wayve is a London-headquartered embodied-AI company developing and licensing mapless, vehicle-agnostic driving software for assisted, automated, and robotaxi applications.
About Wayve
Wayve Technologies Ltd. develops the Wayve AI Driver, an end-to-end, data-trained software platform that runs on onboard vehicle compute and native sensors. It is designed for OEM integration across L1 driver assistance through L4 automated driving, without HD maps.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead technical program management for the data organization. You will deliver data platform, pipeline, enrichment, curation, labelling, and dataset-quality programs; build and coach a TPM team; establish governance and delivery practices; manage risks and dependencies; and connect delivery to quality, throughput, cost, and time-to-insight outcomes.
Requirements
- 8+ years delivering data programs as a technical program manager
- People and process leadership experience
- Experience building or scaling a program function
- Knowledge of data platforms, pipelines, and large-scale data infrastructure
- Experience with petabyte-scale distributed data platforms
- Knowledge of data ingestion and directed acyclic graphs
- Understanding of machine learning, GPUs, model training, and inference
- Proficiency with Databricks, Flyte, Ray, Kubernetes, Azure, Docker, or Python
- Proficiency with AI agents including Cursor, Claude, or Codex
- Cross-functional leadership across data, machine learning, and engineering
Responsibilities
- Build, coach, and grow a TPM team
- Partner with data leadership on roadmap planning, prioritization, and execution
- Lead data platform, pipeline, enrichment, curation, labelling, and dataset-quality programs
- Establish planning cadences, governance, KPIs, dashboards, escalations, and operational reviews
- Align data, machine learning, engineering, and external annotation suppliers
- Manage dependencies, risks, and trade-offs
- Connect delivery to data quality, throughput, cost, and time-to-insight outcomes
- Represent the data organization in company-level reviews
Benefits
- Hybrid working policy with office, workshop, and home working
