Product Quality Engineer, Automotive Sensors

Waymo•Mountain View, CA

1d•$210,000 - $259,000•Remote

About The Position

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. 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.

Requirements

Bachelor's degree in Electrical, Optical, Mechanical, Computer Engineering, or a related field.
10+ years of automotive industry experience in design/hardware engineering for automotive product development, focusing on ADAS/autonomous sensors.
Proficiency in core quality tools and methodologies: APQP, PPAP, FMEA, MSA (Measurement System Analysis), SPC (Statistical Process Control), DOE and 8D problem-solving.
Working knowledge of automotive quality and safety standards (IATF 16949, ISO 26262).
Experience with data analysis, statistical tools, and quality control systems
Excellent cross-functional communication skills with the ability to translate complex engineering issues to leadership and external suppliers.

Nice To Haves

Master's degree in Electrical, Mechanical Engineering, or a related field
Six Sigma Black Belt Certification.
Demonstrated experience in one or more of the following areas: New Product Introduction, Design Engineering, or Manufacturing Operations in consumer electronics
Strong understanding of electronic development processes.
Solid grasp of statistical analysis and production control processes
Proficient in data analysis and interpretation
Experience collaborating with international contract manufacturers in mass production, including travel to manufacturing sites
Knowledge of sensor calibration processes and end-of-line (EOL) testing methodologies.

Responsibilities

Serve as the quality champion across the autonomous driving sensor development team (Cameras, Radars, Lidars), driving design methodologies and executing end-to-end quality plans (APQP and PPAP) from concept through mass production to ensure robust, reliable sensor modules that meet specifications.
Verify and enforce full compliance with the Engineering Requirement Specification (ERS) and sensor specification matrices; oversee the product design lifecycle by facilitating DFMEA, PFMEA, design reviews, DFM/DFA, and DFx for optical, RF/mmWave, and electro-mechanical sensor assemblies.
Partner with optical, RF, hardware, firmware, and test engineering teams to define and validate sensor calibration, active alignment, RF/antenna performance, and End-of-Line (EOL) functional test coverage, limits, and Measurement System Analysis (MSA/GR&R).
Perform hands-on initial failure analysis (FA) and hardware/system debug for Camera and Radar modules, supporting sensor module bring-up and vehicle integration while driving cross-functional 8D root-cause investigations and corrective/preventive actions (CAPA) to closure.
Collaborate with engineering, manufacturing, supply chain, and Tier-1/contract manufacturing partners to execute quality plans, conduct process audits and product inspections, and ensure strict compliance with automotive quality, reliability, and safety standards (IATF 16949, ISO 26262, AEC-Q100/Q200, ASPICE).
Establish and monitor manufacturing yields, defect rates (DPPM), Cp/Cpk, and reliability metrics; apply statistical tools (SPC, DOE) to analyze data from early development, reliability qualification, production, and field operations to drive continuous improvement and incorporate lessons learned into the Sensors PDP.