Senior Optical Engineer, XR

Google•San Jose, CA

7d•$159,000 - $231,000

About The Position

As a Senior Optical Engineer with experience in optics and display hardware development, you will lead the development and manufacturing of cutting-edge optical systems. You will be instrumental in bridging the gap between optical design and high-volume production, ensuring the successful realization of next-gen augmented reality eyewear displays. For decades, the computing revolution has reshaped our world driven by breakthroughs in compute, connectivity, mobile, and now, AI. Google's XR team is at the forefront of the next major leap – the convergence of AI and XR. This is more than just new devices – it's about reimagining how we interact with the world around us. We're building a future where lightweight XR devices like smart glasses and headsets pair with helpful AI to augment human intelligence, offering personalized, conversational, and contextually aware experiences.

Requirements

Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
4 years of experience working in the AR/VR optical system, waveguide display system, or optical semiconductor manufacturing field for waveguide.
Experience in optical design and simulation.

Nice To Haves

Experience with AR, virtual reality (VR), or heads-up display (HUD) optics.
Experience managing the complete optical design lifecycle from design, optimization, analysis, tolerances, fabrication, and metrology.
Familiarity with LightTools, Zemax or equivalent.
Analytical and problem-solving skills, with a data-driven approach.
Communication and cross-functional collaboration skills.

Responsibilities

Design and simulate the next generation waveguide display systems.
Collaborate with optical system, and manufacturing teams to ensure design for manufacturability (DFM) and process integration.
Design and execute experiments (DOE) to characterize process parameters, identify critical process controls, and optimize manufacturing performance.
Utilize statistical process control (SPC) and data analysis techniques to monitor process stability, identify deviations, and drive continuous improvement.
Conduct root cause analysis for process issues, yield loss, and quality defects, and implement effective corrective and preventive actions.