Applied Intuition
Sensor Validation Engineer (Sunnyvale, CA)
About this role
Applied Intuition is seeking a Sensor Validation Engineer to lead validation and characterization of Lidar, Radar, Camera, and Ultrasonic sensors for autonomous vehicle products. You'll develop ML and physical models to improve simulation fidelity while comparing real-world sensor performance against synthetic simulations across automotive, trucking, and construction industries.
What you'll do
- Execute validation protocols for multiple sensor types across diverse operating environments
- Develop and refine ML and physical models of sensing systems to improve simulation accuracy
- Conduct physical sensor performance validation for self-driving system stacks
- Analyze sensor performance metrics and compare hardware data against simulated models
- Collaborate with engineering teams to bridge physical sensor data and synthetic model development
- Automate sensor validation test suites and process large-scale autonomous vehicle datasets
What they're looking for
- Python for data analysis and automation
- Sensor validation and characterization (Camera, Lidar, Radar)
- Linux/Unix and command-line interface proficiency
- Shell scripting (Bash)
- Sensor driver development
- UDP architecture and raw sensor data parsing
- Machine learning model development
- Autonomous vehicle systems knowledge
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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.
- Website
- appliedintuition.com
Likely interview questions
- Describe your experience validating and characterizing sensors like Lidar, Radar, or Camera—what metrics did you focus on?
- How have you used Python to automate sensor validation test suites or process large autonomous vehicle datasets?