Software Engineer, Data Flywheel 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 build and scale data curation, enrichment, evaluation, training, and serving infrastructure. You will turn one-off workflows into self-service products, operate reliable data-platform systems, and partner with scientists and machine learning engineers to take research prototypes into production.
Requirements
- Production software engineering experience
- Production Python experience with services, APIs, and large-scale data processing
- Experience owning and extending large codebases
- Experience with large-scale data and distributed systems
- Experience with batch and streaming pipelines
- Experience with workflow orchestration
- Experience with distributed processing
- Experience designing reliable, observable, high-throughput data or machine learning systems
- SQL, query optimisation, and performance optimisation skills
- Experience shipping and operating production systems
- Experience with testing, code review, observability, and on-call
- Computer science fundamentals and several years of production experience
- Experience with machine learning platforms or MLOps
- Experience with foundation models, world models, or machine learning evaluation
- Experience with embedding and vector search, annotation tooling, or data catalogs
- Experience with Kubernetes and lakehouse stacks
- Experience with autonomous driving, robotics, or sensor-data workflows
Responsibilities
- Build and scale data curation and enrichment pipelines
- Build foundation-model evaluation infrastructure
- Build and optimise training and serving infrastructure
- Build distributed data-processing and data-platform systems
- Create self-service and reliable products from one-off processes
- Own testing, observability, and on-call responsibilities
- Partner with applied scientists and machine learning engineers to productionise research
