Skip to content
Senior/Staff Systems Engineer – Perception System Verification and Validation
| Company | Zoox |
|---|
| Location | San Mateo, CA, USA |
|---|
| Salary | $189000 – $273000 |
|---|
| Type | Full-Time |
|---|
| Degrees | Bachelor’s |
|---|
| Experience Level | Senior, Expert or higher |
|---|
Requirements
- B.S. or higher degree in Automotive Engineering, Aerospace, Robotics, Electrical, Mechanical, Systems Engineering, Computer Science, or a relevant field
- Experience managing small teams of direct reports
- 7+ years of industry experience working on complex systems (hardware and software) that feature perceptive components (cameras, radar, LIDAR, etc.)
- Demonstrated experience with integration and verification testing of ML components (classifiers, detectors, regression models, encoder/decoders, etc.)
- Proficiency in basic statistics and probability
- Experience with test scripting and data analysis languages (Python and SQL preferred)
- Ability to manage ambiguity and drive progress independently
- Strong communication skills and ability to work well with cross-functional teams
Responsibilities
- Measure the safety performance of the driving software perception algorithms, and their impact on the resulting behavior across nominal conditions, adverse weather conditions, and corner case scenarios.
- Leverage fleet data, structured test track evaluations, log replay simulations, and novel synthetic simulations to produce an argument for the Zoox Safety Case.
- Develop new methodologies to improve test coverage, robustness, and scale
- Manage a small team of systems verification engineers
- Collaborate cross-functionally with hardware, perception, simulation, compute infrastructure, and operations teams to execute test campaigns, develop new processes, and troubleshoot mission critical findings
- Perform test data analysis and report test results. Maintain traceability between requirements, test cases, and results. Define and develop automated data extraction tools to streamline analysis and reporting.
Preferred Qualifications
- Experience with Linux Systems
- Experience in the Autonomous Vehicle Domain
- Experience with applying machine learning techniques or other novel approaches to test campaigns to augment the scale and coverage of more traditional test methodologies.
- Experience working on the assurance of safety-critical systems
