Software Engineer, Data Enrichment

In this role you will design, build and operate the backend and data-processing components of Wayve’s Data Enrichment Platform. You will enable model engineers to deploy and evaluate scalable workflows across petabytes of driving data on GPU fleets. You’ll improve reliability, cost efficiency and observability while collaborating with cross-functional teams to deliver reusable capabilities. This is a hands-on, production-focused role with a strong emphasis on system design and impact on autonomous driving outcomes.

• salary benchmarks against market
• meaningful equity
• relocation support and visa sponsorship
• hybrid working with core hours
• learning and development budgets
• comprehensive health benefits including health insurance and dental, enhanced parental leave, retirement/pension, wellbeing support

• 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 scalability and reliability 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
• Contribute to designs covering data locality, scheduling, capacity, backpressure, failure recovery and observability
• 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, operational tooling and engineering standards
• Work on a scalable platform for large-scale inference, automated evaluation, model monitoring, active learning and retraining
• Build backend services and APIs for repeatable workflows
• Develop reproducible dataset selection, versioned outputs, and annotated datasets with provenance and lineage
• Ensure reliable model-execution workflows across large data and GPU fleets
• Develop monitoring and operational tooling for platform reliability, throughput and cost
• Contribute to continuous evaluation, drift detection and automated model-improvement loops across robotics and computer-vision workloads

• Strong production software-engineering experience in Python
• Experience designing, building or operating distributed data-intensive or compute-intensive systems
• Proven track record delivering reliable software from design to production
• Solid system-design fundamentals and ability to trade off within a complex platform
• Comfort investigating unfamiliar systems and diagnosing reliability/performance issues
• Clear communication and collaboration with cross-team ownership of production components
• Experience with Flyte, Airflow, Dagster, Argo, Spark, Databricks, Ray, Kubernetes, GPU infrastructure or ML-platform systems (advantage)
• Hands-on experience with robotics, autonomous-vehicle or computer-vision datasets (sensor data, annotations or model outputs) (advantage)
• Understanding of 3D geometry for robotics/computer vision (coordinate frames, transformations, calibration, projection) (advantage)
• Experience validating sensor data or model outputs and checks for correctness (advantage)
• Experience with 3D object detection, segmentation, tracking or ego motion (advantage)

• Clear communication
• Cross-team collaboration
• Ownership of production components
• Python production backend services
• Distributed systems for data-intensive workloads
• Model-execution workflows and data provenance