Perception Validation Engineer
On-siteSanta Clara, California, United States
Job Summary
Define validation metrics and performance benchmarks for camera, LiDAR, and radar perception stacks. Build automated regression testing pipelines to evaluate algorithms on massive real-world and synthetic datasets. Oversee ground truth generation using automated labeling and manual curation while mining edge cases like sensor degradation to stress-test the system. Partner with the Perception ML team to debug failures, trace root causes, and close the loop with model training. Develop realistic sensor models and synthetic scenarios to bridge simulation and reality. Generate comprehensive verification reports to support safety cases and regulatory compliance. Requires a Bachelor's or Master's in a quantitative field, 2+ years in robotics validation, and strong Python or C++ proficiency. Full-time role in San Francisco with competitive salary and comprehensive benefits.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Robotics, Electrical Engineering, Aerospace Engineering, or a related quantitative field
- 2+ years of professional experience in testing, validation, or development of robotics/autonomous systems, or computer vision models
- Strong proficiency in Python (especially NumPy, Pandas, Pytest) and/or C++
- Experience manipulating and visualizing large scale datasets (SQL, data lake queries) and utilizing statistical methods to evaluate model performance
- Solid understanding of core computer vision concepts, deep learning principles, and spatial geometry (3D transformations, coordinate frames)
Desired Qualifications
- Experience with ROS / ROS2
- Familiarity with cloud computing infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
- Experience with machine learning frameworks (PyTorch) and validation tools
- Understanding of functional safety standards in automotive engineering (e.g., ISO 26262, ISO 21448 / SOTIF)
- Experience working with CI/CD pipelines (Jenkins, Github CI) for automated testing
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