Platform Engineer, Data Enrichment for Autonomous Driving

Wayve; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Equity

Hybrid work

Relocation support

Learning budget

Health insurance

Job summary

Wayve is seeking a skilled backend software engineer to build and operate data-processing workflows for the Data Enrichment Platform. You will work on model-execution workflows, dataset catalogues and annotation features that power large-scale inference across petabyte-scale data and GPU fleets.

You will collaborate with cross-functional teams to ensure reliability, observability and cost efficiency, while writing clean, tested code and improving documentation.

Qualifications

• Strong production software engineering experience in Python.
• Experience designing, building or operating distributed data workloads.
• Ability to design reliable systems and reason about trade-offs.
• Comfortable investigating unfamiliar systems and diagnosing issues.

Responsibilities

• Design, build and operate backend services, APIs and data-processing workflows for the Data Enrichment Platform.
• Develop model-execution workflows, versioned outputs, annotation capabilities and dataset-catalogue features.
• Improve the scalability and reliability of systems for large-scale inference, automated evaluation and model monitoring.
• Investigate and resolve reliability, performance and cost issues across petabyte-scale data and GPU-backed workloads.
• Collaborate with model engineering, AI Platform, infrastructure, compute, storage and data teams to deliver reusable capabilities.
• Write maintainable, tested and observable software while improving documentation and tooling.

Skills

Python backend

Distributed systems

System design

Production operations

Troubleshooting

Collaboration

Tools

Flyte

Airflow

Kubernetes

Spark

Databricks

Job description

Wayve is seeking a skilled backend software engineer to build and operate data-processing workflows for the Data Enrichment Platform. You will work on model-execution workflows, dataset catalogues and annotation features that power large-scale inference across petabyte-scale data and GPU fleets.

You will collaborate with cross-functional teams to ensure reliability, observability and cost efficiency, while writing clean, tested code and improving documentation.