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Applied Intuition

Autonomy Verification Engineer

Sunnyvale$120k–$180kfulltimemidAdded 1 month ago

About this role

Applied Intuition seeks an Autonomy Verification Engineer to evaluate and validate autonomy systems for Level 4 trucking. You'll develop validation strategies, create datasets, and build performance metrics frameworks across perception, planning, prediction, and localization modules.

What you'll do

  • Develop system validation strategies for autonomy modules (perception, planning, prediction, localization)
  • Build comprehensive datasets from simulations and real-world data
  • Collaborate with systems engineering on validation test plans and ODD coverage
  • Create statistical and ML models for safety performance analysis
  • Define, measure, and report performance metrics
  • Build and deploy frameworks/pipelines for metric generation and support safety case documentation

What they're looking for

  • ADAS and autonomous driving systems
  • Validation and verification testing
  • Statistical analysis and machine learning
  • Automotive safety standards (ISO 26262, ISO 21448, UL4600)
  • ADAS/AV system architecture
  • Simulation tools and scripting
  • Python and/or C++
  • Cross-functional collaboration

Benefits

  • Base salary $120,000 - $180,000 USD annually
  • Equity (options and/or restricted stock units)
  • Comprehensive health, dental, vision, life and disability insurance
  • 401k retirement with employer match
  • Learning and wellness stipends
  • Paid time off
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Applied Intuition

Applied Intuition builds autonomous vehicle and defense systems software, including motion planning algorithms, simulation infrastructure, and autonomy integration platforms for aerial and ground platforms. The company is hiring for security engineers, robotics/autonomy software engineers, hardware-in-the-loop specialists, and IT operations professionals to support its growing physical AI operations.

View all jobs at Applied Intuition

Likely interview questions

  • Walk us through your experience validating ADAS or autonomous driving systems. What modules (perception, planning, prediction, localization) have you worked with, and what validation challenges did you encounter?
  • Describe your experience developing test strategies and datasets for autonomous vehicles. How do you ensure test coverage across different operational design domains (ODD) and vehicle behaviors?