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

Lead the autonomy performance for Robotaxi, connecting technical metrics to product outcomes, while overseeing performance measurements, debugging, and cross-functional team execution.

The ADAS Feature Engineer will develop C++ software for ADAS features, working with AI outputs and vehicle behavior, conduct testing, and collaborate with various teams to ensure quality and safety in automated driving systems.

The Technical Product Manager is responsible for defining and delivering L4 autonomous driving solutions, aligning with stakeholders and overseeing product development from concept to deployment.

Lead the architecture and technical roadmap for Remote Assistance in robotaxi systems, ensuring safety, reliability, and effective cross-team collaboration.

Maintain and improve reliability, availability, and performance of vehicle software across the dev fleet. Build monitoring, logging, alerting, and on-call tooling; run incident response and postmortems; automate deployments and fleet operations; partner with Vehicle SW and platform teams to define SLOs and harden production environments.

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.

Manage the applied methods Data Science team supporting autonomous driving. Set priorities and roadmaps, review technical designs, ensure statistical rigor, manage delivery, hire and develop data scientists, scale tooling and automation, and build strong relationships with Autonomy stakeholders and customers. The role requires causal inference expertise and experience leading high-performing teams, with desirable experience in ML, simulation, offline evaluation, distributed computing, and productionizing research.

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.

Own the global external partner network supporting fleet operations across multiple markets. Manage partner relationships, contracts, commercial terms, KPIs, compliance, onboarding, transitions, and performance reviews. Source and evaluate new partners, resolve operational issues, and develop scalable partnership playbooks and performance frameworks. Provide commercial and partnership support to Robotaxi operations teams while coordinating with Fleet Operations, Safety, Legal, Finance, and leadership.