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Wayve is building an AI platform for autonomous driving using end-to-end learning approaches. This Test Engineer role is based in Leonberg, Germany, and focuses on localizing and advancing Wayve's autonomous driving technology for the German market.
You will independently own the design and delivery of automated verification for a defined area of the embedded software stack. This is a hands-on delivery role where you'll build robust, reusable test automation, drive failures to root cause across engineering boundaries, and steadily raise the bar on coverage, reliability, and traceability. As the company and your experience evolve, you'll have room to grow into broader areas including sensing and model-behavior testing.
Day-to-day responsibilities include:
- Develop automation for system functionality tests at component, integration, and system levels across software and hardware boundaries
- Automate open-loop and closed-loop replay-based tests, reliability and fault-injection tests to support verification, release, coverage expansion, and debug workflows
- Lead root-cause investigations for failures found during test campaigns, collaborating across hardware, software, and infrastructure teams
- Optimize Buildkite CI/CD-integrated test workflows for rapid, reliable, and repeatable execution
- Integrate third-party verification tools including JAMA (requirements), MC/DC (coverage), and MISRA (style compliance); manage artifacts via Artifactory and Azure
- Define and track KPIs and quality metrics for system testing, supporting data-driven validation and release decisions
- Uncover software and hardware bugs through increased test coverage and report findings through JIRA
- Identify and implement infrastructure improvements that enhance test coverage, failure traceability, and compliance reporting
- Review, create, and adhere to Risk Assessments to ensure all testing activities are conducted safely and responsibly
Wayve operates a hybrid working model with main hubs in London, Sunnyvale, Yokohama, Herzliya, Vancouver, and Leonberg. The company offers relocation support and visa sponsorship where applicable, learning and development budgets, comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement/pension, access to therapists, and wellbeing partnerships.
REQUIREMENTS:
Essential Skills & Experience:
- Hands-on experience with system-level verification and validation in robotics, embedded software, or mechatronic systems, with a track record of delivering test automation independently
- Experience with L2+ hands-off, L3, or L4 automated driving systems
- Knowledge of consumer safety-rating protocols (e.g., Euro NCAP-AEB, LSS/LKA, ADAS scenarios), DCAS regulatory testing (UN R171), and automotive cybersecurity testing and standards (ISO/SAE 21434, UN R155)
- Experience with HiL testing and tooling using CAN, Ethernet, GMSL, dSPACE, Vector, Xylon, or similar
- Strong proficiency in Python, including developing automation test frameworks with pytest
- Proven ability in interface-level testing, including hardware/software interactions and embedded interfaces
- Experience integrating software quality assurance tools and standards (ASPICE, SOTIF, ISO 26262, JAMA, X-RAY)
- Knowledge of open- and closed-loop HiL replay using dSPACE or other emulators
- Proficient in CI/CD principles and related tooling (e.g., GitLab CI, Buildkite, Bazel)
- Experience with test automation dashboards, logging, and reporting infrastructure (e.g., Grafana, Looker, Datadog, JIRA)
- Experience developing or testing automotive software across embedded and system levels
- Strong cross-functional communication skills; able to work collaboratively across software, hardware, autonomy, DevOps, and product teams
Desirable Skills & Experience:
- Experience with autonomous vehicle systems, ADAS, or related technologies
- Strong Python automation and knowledge of dSPACE open and closed-loop HiL-based replay testing
- Experience contributing to continuous improvement of test methods, safety procedures, or operational efficiency
- Awareness of data management and version control systems (e.g., Git, Buildkite, or similar)
- Familiarity with agentic AI coding tools (e.g., Cursor, Claude Code) and demonstrated ability to use them to accelerate and optimize test development, debugging, and automation workflows
