XPENG
smart technology
StaffAutonomousSystemTestEngineerVLA
“Staff Autonomous System Test Engineer - VLA at XPENG. Skills: Autonomous System Test Engineer, autonomous driving systems, ML-based systems, validation plans, simulation testing, vehicle testing, issue triage, root-cause analysis, scenario design, simulation validation, real-world vehicle testing, GenAI/ML-powered workflows, tooling development. Partner closely with MLEs to understand newly developed features and define customized validation plans for both simulation and vehicle testing. Triage,”
What You'll Achieve.
ensure new VLA capabilities are robust, reliable, and production-ready; shape the quality of autonomous driving features; accelerate debugging and iteration cycles; ensure sufficient validation exposure for new capabilities and prevent regression of existing capabilities; improving test consistency; ensure detailed behavior coverage; improve triage efficiency, issue analysis, and testing productivity; accelerating iteration velocity while maintaining quality and safety standards
Industry & Context.
highly analytical; systems thinking; hands-on debugging capability; debugging and root cause analysis skills for complex system behaviors; Identify patterns and potential root causes behind failures, regressions, or unstable driving behaviors; Structured thinking and the ability to operate effectively under ambiguity
requires up to 4 weeks of travel per quarter
What They're Looking For.
Must Have
Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or a related technical field, Experience in autonomous driving system testing, robotics testing, or ML system validation, understanding of machine learning system behavior and autonomous driving workflows, Experience with simulation-based testing, scenario generation, or validation pipelines, debugging and root cause analysis skills for complex system behaviors, Excellent communication and cross-functional collaboration skills, Ability to work in fast-paced and highly iterative development environments
Nice to Have
Experience working with VLA, end-to-end driving models, or multimodal ML systems, Familiarity with closed-loop simulation systems and autonomous vehicle evaluation methodologies, Experience with data analysis tools such as Python, SQL, or visualization frameworks, Experience designing testing infrastructure, evaluation pipelines, or automated regression systems, Familiarity with vehicle logs, sensor data analysis, and autonomous driving metrics, Experience building internal tooling using LLMs, GenAI agents, or ML-assisted workflows, Hands-on experience participating in vehicle testing operations
What You'll Do.
Partner closely with MLEs to understand newly developed features and define customized validation plans for both simulation and vehicle testing
and root-cause autonomous driving issues across simulation and road testing environments
Categorize issues by feature area
and potential ownership to accelerate debugging and iteration cycles
Distill complex system behaviors into actionable insights and provide clear debugging directions for MLEs and cross-functional teams
Identify patterns and potential root causes behind failures
or unstable driving behaviors
Continuously adapt testing plans based on daily feature development progress to ensure sufficient validation exposure for new capabilities and prevent regression of existing capabilities
Work closely with vehicle testing teams to coordinate and influence on-road testing plans
minimizing environmental noise and improving test consistency
and customize driving scenarios into scalable simulation test suites to ensure detailed behavior coverage
Drive improvements in standardized on-road testing methodologies and contribute to the design of closed-loop simulation testing frameworks
Design and develop GenAI/ML-powered workflows and tooling to improve triage efficiency
and testing productivity
Participate regularly in in-vehicle testing missions to evaluate real-world behavior of autonomous driving features
How You'll Work.
Team & Collaboration
Partner closely with MLEs; provide clear debugging directions for MLEs and cross-functional teams; Work closely with vehicle testing teams to coordinate and influence on-road testing plans
Communication Scope
Excellent communication and cross-functional collaboration skills; provide clear debugging directions
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