Senior Software Engineer, Data
Full-time
Wayve
Before the detail, here's the challenge you'd help us solve.
We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.
Here’s what this particular role covers. The role Portal is the cloud platform that connects Wayve to the outside world: handling data exchange with partners, surfacing AI insights, and enabling the commercial deployment of Wayve's AI driver on vehicles across the globe. We're looking for a Senior Software Engineer, Data to help build Wayve's Data Transfer Hub : a mission-critical piece of infrastructure that will scale to transfer petabytes of sensor data per day from partners covering vehicles around the world. This is a pivotal project at Wayve. You'll work as part of a small, high-autonomy team building a globally distributed hub-and-spoke data exchange system, working with partners like Uber, Stellantis and Nissan. Your work will help make Wayve's AI model training possible at scale. Key Responsibilities- Build and operate large-scale data transfer pipelines for video, LiDAR and sensor data from global partners at up to PB/day scale
- Contribute to the technical design of the Data Transfer Hub, making pragmatic trade-offs across UX, careliability, throughput, cost, partner constraints, observability and operational support
- Build parallelised, distributed data transfer pipelines using Flyte for workflow orchestration, Kafka/event-driven patterns for lifecycle tracing, and Azure for storage and transfer infrastructure
- Help implement and evolve a globally distributed hub-and-spoke data transfer model to retrieve and share sensor data at scale with partners
- Write infrastructure-as-code in Terraform and pipeline logic primarily in Python
- Build reliable operational foundations, including retry strategies, backfills, data integrity checks, lifecycle/state tracking, dashboards and alerting
- Work on cloud-to-cloud and cross-cloud networking solutions, with Azure as the primary cloud platform
- Once established, participate in an out-of-hours on-call and support rotation.
- Collaborate with product, commercial and partner-facing teams to understand constraints and deliver solutions that solve real customer and partner problems
- Work in a fast-changing environment where requirements and partner deliverable dates evolve, while maintaining high engineering standards
- Proven experience building and operating large-scale data transfer, ingestion or data processing pipelines, ideally at multi-TB or PB scale
- Strong software engineering skills
- Experience delivering & maintaining production systems
- Experience with workflow orchestration for parallelised jobs; Flyte preferred, but Airflow, Prefect or similar tools are also relevant
- Experience building reliable, observable data systems, including retry strategies, backfills, data integrity checks, lifecycle/state tracking and operational alerting
- Strong cloud platform skills, with Azure preferred; experience with AWS or GCP is a plus
- Proficiency in Python and Terraform
- Experience with blob/object storage, large-scale file movement, networking or cloud-to-cloud data transfer
- A product mindset: you think about the customer and build solutions that fix real problems, not just implement requirements
- Comfort working in a fast-changing environment with evolving requirements
- A strong sense of ownership: you take responsibility for outcomes, communicate clearly, and help the team move quickly
- Experience working with external data partners or customer-facing technical integrations
- Background in autonomous vehicles, robotics, geospatial data, video processing or other data-intensive domains
- Experience with Kafka or other event-driven systems for transfer observability and lifecycle tracking
- Experience building dashboards to communicate transfer job status
- Multi-cloud experience across Azure, AWS and/or GCP
- Experience improving cost efficiency, throughput or reliability of large-scale cloud data systems
Vacancy posted 3 days ago
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