Jobs at Wayve

Provide hands-on technical support for integrating Wayve's autonomous driving software into customer vehicles, troubleshoot system-level issues, liaise between customer integration teams and internal engineers, use diagnostic/calibration tools, and support development through validation to production readiness.

The Technical Program Manager drives portfolio projects, aligns cross-functionally with teams, manages product roadmaps, and maintains executive communication to deliver value and achieve growth goals.

Own end-to-end supply chain execution for assigned programs, including prototype development and NPI. Lead material planning, BOM translation, supplier management, compliance, risk mitigation, upfitter coordination, and KPI reporting to ensure program timelines and build readiness.

The Software Integration Engineer will integrate AI software stack on customer hardware, support system diagnostics, and enhance automotive software performance.

Perform software bring-up and early validation of Wayve's AI stack on customer automotive hardware. Integrate drivers, middleware and runtimes, automate flashing and health checks, add diagnostics and secure-boot, and integrate platforms into CI/CD, HIL and test infrastructures while collaborating with OEMs, Verification and Release teams.

As a Staff Machine Learning Engineer, you will lead the development and deployment of AI models for autonomous driving, focusing on safety and reliability. Responsibilities include driving the roadmap, training models, and collaborating across teams.

The Application Software Engineer will focus on integrating AI technology for autonomous driving, ensuring software functionality on hardware platforms, and collaborating across teams for smooth delivery.

The Principal Application Software Engineer will lead the integration and validation of AI software on automotive platforms, focusing on hardware interaction and performance in Japan.

Lead early-stage OEM engagements across Europe, managing RFQ/RFI and bid responses end-to-end. Coordinate product and engineering inputs, craft customer narratives and proposals, present to technical and executive stakeholders, and align internal teams to advance opportunities toward PoC and nomination.

The Technical Operations Manager will bridge Science, Product, Engineering, and Operations, driving technical strategies into effective field operations and leading testing and validation programs.

Lead ownership of the vehicle sensing subsystem: define sensing requirements, drive sensor architecture and integration, build validation frameworks, set benchmarks and acceptance criteria, diagnose sensor issues, and partner with ML, Hardware, Vehicle SW and Product to ensure reliable on-road performance.

Design and lead the embedded software architecture for Wayve's autonomy platform. Develop prototypes and reference implementations, optimize system performance and reliability, collaborate with AI, platform, and vehicle teams and external partners (NVIDIA, Qualcomm, OEMs), drive modern development practices for high-assurance embedded software, mentor senior engineers, and represent Wayve in external technical discussions.

Deliver production-ready ML model releases: train and iterate PyTorch models, evaluate and debug performance, apply optimizations (quantisation, distillation), collaborate with performance and deployment teams, and ensure models meet tight on-vehicle runtime constraints.

Optimize transformer-based ML inference for edge accelerators and GPUs. Implement and validate compiler, runtime, and kernel optimizations; profile end-to-end inference stacks; build benchmarking and regression tests; target multiple platforms (NVIDIA, Qualcomm); collaborate with model developers and cross-functional teams to deliver performant, maintainable on-vehicle ML systems and contribute to technical roadmaps.

Lead and operationalize on-road ADAS testing in Eastern North America. Translate strategy into tactical plans, manage shift leads and resource allocation, deliver testing outputs and performance metrics, liaise with cross-functional teams, implement continuous improvement, and ensure safety and operational efficiency.

Define and manage technical architecture for integrating Wayve's autonomous driving software with OEM/Tier1 vehicle systems. Translate product and customer needs into interface contracts, ownership boundaries, integration specifications, test requirements, and program-facing documentation. Coordinate across Product, Software Architecture, Validation, and customer teams and represent Wayve in OEM/Tier1 technical discussions to identify risks, dependencies, and validation criteria.

The Machine Learning Engineer role at Wayve focuses on leading initiatives in model-based autonomous driving, involving the development and delivery of ML-driven behaviors, collaboration across teams, and mentoring other engineers.

Lead and grow a TPM function for the Data org, owning delivery of data platform, ingestion, pipelines, enrichment, labeling, and dataset quality. Drive flagship programs, establish scalable governance and KPIs, coordinate cross-functional dependencies, and partner with engineering to improve data quality, throughput, cost, and time-to-insight.

Develop, train, evaluate, and iterate CV and 3D perception models for ADAS. Build scalable data pipelines (including auto/pseudo-labelling), improve detection/segmentation/tracking, and own end-to-end dataset generation and evaluation to improve real-world driving performance.

Analyze real-world autonomous vehicle run data to identify root causes, produce top-issue reports, validate triage automation, and collaborate with Detective and Triage engineers to drive issue resolution, documentation, and process improvements to maintain ADAS safety and reliability.