Hardware Engineering is an innovative and collaborative group of electrical, mechanical, reliability, software and vehicle engineers. We design, build, and perfect the products which are the eyes and ears of Waymo's autonomous driving technology, and integrate those products into vehicle platforms. We're seeking curious and talented teammates to keep us moving in the right direction.

This role follows a hybrid work schedule, and you will report to the Tech Lead Manager of the Sensor Software Team.

You will:

• Work in a multidisciplinary team environment including lidar, radar, camera, or other sensor architecture design, embedded control, GPU digital signal processing, test, and manufacturing
• Design and execute comprehensive Image Quality (IQ) test plans for new camera hardware and ISP (Image Signal Processor) pipeline, covering standard metrics and machine learning-specific criteria
• Automate processing, analysis, reporting, and visualization of image data collected from lab setups and self-driving vehicles to enable fast, data-driven decisions on image quality tuning and system performance
• Understand and evaluate internal and external quantitative image quality metrics, and apply them to guide improvements in sensor and ISP for downstream machine learning tasks
• Collaborate closely with the Sensor, ISP, Perception, and System Engineering teams to drive hardware/software co-optimization, providing concrete data and analysis that guides design trade-offs and component selection
• Investigate and debug complex image quality issues, artifacts, and data anomalies across the entire imaging pipeline, from sensor physics through to machine learning inference

You have:

• BS in Computer Science, Computer Engineering, Electrical Engineering, Math, or Physics (MS or PhD preferred for Math and Physics majors)
• 5 years experience in production code software development in a complex, multiple team environment
• Expertise in C++ and familiarity with Python
• Familiarity with image signal processing SW and HW

We prefer:

• Familiarity with the fundamentals of CMOS imaging sensors
• Experience with image quality evaluation for both human visual perception and machine learning performance
• Hands-on experience with computer vision
• Familiarity with SQL or NoSQL databases for querying and analyzing large datasets of test results and vehicle logs
• Experience with sensor testing and calibration procedures used in the sensor module manufacturing process
• Familiarity with self-driving technology