Senior Software Test Engineer, L3 and L4 - Autonomous Driving

NVIDIA NVIDIA · Semiconductors · Munich, Germany

Senior Software Test Engineer for L3 and L4 autonomous driving products at NVIDIA. Responsibilities include developing test strategy, defining test plans, formulating test cases, collaborating with stakeholders, leading vehicle integration, and spearheading data triage and root cause analysis. Requires extensive experience in ADAS, system analysis, data analysis, software architecture, and mass-production launches of autonomous driving features, with a strong understanding of functional safety and AV sensor suites.

What you'd actually do

  1. Develop test strategy and use cases/scenarios for L3 and L4 autonomous driving products based on customer needs, traffic regulations, certification standards, and industry guidelines.
  2. Define test strategy and execution plan on vehicle platform.
  3. Formulate test cases and define critical performance metrics to ensure compliance with functional and safety requirements.
  4. Close collaboration with different stakeholders to define the KPIs and evaluate the product progress by closing the loop with test data/results.
  5. Lead L3/L4 vehicle integration and retrofitting, managing end-to-end processes to advance testing and validation schedules.

Skills

Required

  • MS or PhD in Engineering, Physics, Computer Science, or a related field (or equivalent experience)
  • 10+ years proven experience in ADAS, system analysis, data analysis, and software architecture
  • 3+ years of experience driving the mass-production launch of autonomous driving products, including supervised FSD, urban NOA, or equivalent features
  • Proficiency in programming languages commonly used in AV development and testing (e.g., Python, C++) and familiarity with data query and analysis tools
  • Awareness of functional safety (ISO 26262), Safety of the Intended Functionality (SOTIF / ISO 21448), and V-model validation methodologies
  • Strong leadership and interpersonal skills, with the ability to drive alignment across large organizations
  • Proven understanding of trade-offs between End-to-End deep learning approaches, classical modular perception/planning stacks, and associated validation and test strategies
  • Deep understanding of autonomous vehicle sensor suites (LiDAR, Radar, Camera, Ultrasonic) and their specific failure modes, edge cases, and validation requirements
  • Provide technical mentorship to junior engineers and lead by example in establishing rigorous testing and validation standards

Nice to have

  • Experience contributing to a launched L3/L4 autonomous vehicle program
  • Hands-on experience with testing strategy for ADAS, large-scale datasets, data analytics workflows
  • Innovation by tools/out of the box thinking to resolve the problem statement

What the JD emphasized

  • mass-production launch of autonomous driving products
  • supervised FSD, urban NOA, or equivalent features
  • functional safety (ISO 26262)
  • Safety of the Intended Functionality (SOTIF / ISO 21448)
  • V-model validation methodologies
  • testing strategy for ADAS
  • large-scale datasets
  • data analytics workflows

Other signals

  • L3 and L4 autonomous driving products
  • mass-production launch of autonomous driving products
  • testing strategy for ADAS
  • large-scale datasets
  • data analytics workflows