Top Tech Jobs & Startup Jobs

The Supply Chain Program Manager oversees end-to-end supply chain execution, ensuring compliance, managing risks, and coordinating across multiple teams for product builds and launches.

Design, develop, and execute automated tests for onboard embedded software across OS, middleware, sensors, and integration points. Validate behavior on embedded hardware and HiL setups, debug system-level issues, build reusable test frameworks, integrate tests into CI pipelines, and enable developer self-service testing to improve coverage and speed release cycles.

Own the roadmap for development and experimentation vehicle platforms, coordinating software, hardware, engineering, program management, and internal stakeholders. Define requirements, workflows, KPIs, and scalable capabilities that accelerate experimentation, data collection, debugging, deployment, and customer programs. The role requires autonomy or AV experience, embedded-platform expertise, systems thinking, stakeholder influence, and cross-functional execution across complex hardware-software environments.

The role involves refining algorithms for stability in autonomous vehicle platforms, troubleshooting system issues, and providing technical support for customer programs.

The Principal Software Engineer - Robot Software leads architectural design, mentors engineers, and influences technical strategy for autonomous vehicle capabilities at Wayve.

Lead commercial execution for robotaxi partnerships and deployments in the US. Manage relationships with ride-hailing platforms, OEMs, and ecosystem partners while coordinating launch readiness across technical integration, fleet ramp, operations, safety, policy, and marketing. Track KPIs, manage risks, support pilot launches, and help scale autonomous mobility services to production vehicles and new markets.

Develop actionable insights for autonomous-driving AI engineering teams through experimental and observational analysis of real and simulated driving. Define performance metrics, design experiments, evaluate statistical results, investigate model training and inference bottlenecks, and identify improvements to functionality, safety, and performance. The role also involves building large datasets with SQL, applying statistical and machine-learning methods, communicating findings, and influencing engineering priorities and strategy.

Build, train, fine-tune, and evaluate computer vision and scene-understanding models for offline autonomous-driving measurement. Improve accuracy and generalization across vehicles, markets, and conditions using large models, temporal context, and multi-task learning. Define ground truth, benchmarks, metrics, and statistically defensible evidence for validation and safety cases. Collaborate across modeling, evaluation, data, and simulation teams while mentoring engineers and driving significant modeling workstreams.

Lead data-centric work for embodied AI: mine and curate fleet driving data, build large-scale enrichment and labeling pipelines, train and fine-tune foundation models, and design rigorous offline and closed-loop evaluation to improve safety and generalization across cities, vehicles, and sensor rigs.

Lead development of 3D geometric vision and world foundation models for autonomous driving. Responsibilities include designing and training deep-learning models, building scalable sensor-data, auto-labeling, SLAM, reconstruction, evaluation, and ground-truth pipelines, and deploying models on production vehicles. The role requires technical direction across geometric vision, multimodal sensing, distributed training, neural rendering, 3D representations, and real-time inference.