Staff Software Engineer Data Enrichment Platform
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 own the technical vision for systems that deploy, run, evaluate, and improve machine-learning models. You will lead backend, API, workflow, data-catalogue, inference, evaluation, monitoring, and retraining capabilities. You will address distributed data and compute constraints, define service metrics, mentor engineers, and drive cross-functional delivery.
Requirements
- Python
- Backend development
- API
- Data processing
- Distributed system
- Data-intensive workload
- Compute-intensive workload
- Platform engineering
- System architecture
- Workflow orchestration
- Flyte
- Airflow
- Dagster
- Argo
- Batch inference
- Machine learning platform
- Model deployment
- Model registry
- Spark
- Databricks
- Ray
- Dataset catalogue
- Metadata
- Provenance
- Versioning
- Lineage
- Kubernetes
- GPU infrastructure
- Cloud architecture
- Model monitoring
- Active learning
- Automated retraining
- Computer vision
Responsibilities
- Define the technical vision and architecture for the Data Enrichment Platform
- Lead development of backend services, APIs, workflows, outputs, annotation capabilities, and dataset catalogues
- Build systems for inference, evaluation, monitoring, active learning, and retraining
- Address data locality, scheduling, capacity, backpressure, recovery, observability, and cost
- Make technology build, buy, reuse, integration, consolidation, and replacement decisions
- Establish technical boundaries across platform functions
- Lead cross-team delivery and mentor engineers
- Define service levels and success metrics