Image Processing Engineer, Home Device

Minimum qualifications:

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Imaging Science, Color Science, or equivalent practical experience.
  
• 2 years of experience in consumer camera image quality development or ISP algorithm development.
• Experience with scripting language Python or coding language C or C++.
  

Preferred qualifications:

• PhD in Electrical Engineering, Computer Science, Imaging Science, Color Science, or a related field.
  
• Experience in machine learning algorithm development.
  
• Experience in coursework in digital image processing or computer vision.
• Knowledge of Complementary Metal-Oxide-Semiconductor (CMOS) image sensors, chip design.
  
• Understanding of Image Signal Processor (ISP) pipeline architecture and individual algorithm blocks.
  
• Understanding of Auto White Balance (AWB) and Auto Exposure (AE) algorithms, color science.
  

In this role, you will work in image quality on Google Nest cameras for surveillance, displays, or other applications. You will engage in product development cycle from the early stage such as vendor System on a Chip (SoC) selection to Image Signal Processing (ISP) performance optimization, automatic exposure/auto white balance algorithm development, and final shipment of the cameras. You will solve issues and ship excellent camera products to the user.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

• Optimize software and hardware parameters for the possible image quality performance on cameras.
• Test automation, tuning, or other tools for improved productivity and quality, including Machine Learning (ML) assisted tools.
  
• Design and implement imaging software development.
• Develop Auto Exposure/Auto White Balance algorithms and implement them.
• Work on Image Signal Processor (ISP) pipeline, including IQ benchmark, architectural review, evaluation of individual algorithm blocks.