Sensor Validation Engineer

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · Autonomy Tooling Software Engineering

This role focuses on validating and characterizing sensor performance for autonomous systems, using both ML and physical models within a simulation environment. The engineer will design tests, develop data collection tools, improve simulation models, and work with customers to validate their models.

What you'd actually do

  1. Design and execute tests for correlation experiments for real and synthetic sensor outputs
  2. Develop the hardware and software components necessary for data collection and analysis
  3. Make improvements to underlying scenes, materials, models to improve simulation
  4. Work with customers to validate their models and integrate with the simulation environment
  5. Write white papers, internal and external documents detailing results

Skills

Required

  • 3+ years of experience
  • Bachelor’s or foreign degree equivalent in Electrical, Mechanical, Robotics Engineering, or a related field
  • Experience in Sensor Validation and characterization, including analyzing performance metrics for sensing modalities such as Cameras, Lidar, or Radar under diverse environmental conditions
  • Technical proficiency in a Linux/Unix environment, including command-line interface (CLI) navigation, shell scripting (Bash), and managing software dependencies for autonomous system stacks
  • Experience in sensor driver development, including the ability to utilize UDP architectures to parse and extract raw sensor data for performance analysis
  • Experience writing software in Python & C++
  • Proficiency in Python for data analysis, automation of sensor validation test suites, and processing large-scale datasets from autonomous vehicle sensors

Nice to have

  • Understanding and knowledge of physical processes by which a sensor operates
  • Hands on experience with characterization of simulated sensor models for Lidar, Radar, and Camera
  • Competence in linear algebra, antenna theory, optics, circuits, photonics, electro-optics
  • Experience/familiar with computer graphics technologies such as raytracing, deferred rendering, physically-based rendering

What the JD emphasized

  • sensor validation and characterization
  • analyzing performance metrics for sensing modalities
  • Python for data analysis, automation of sensor validation test suites, and processing large-scale datasets

Other signals

  • sensor simulation
  • ML models
  • physical models
  • autonomous perception systems