Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 1 year of experience with software development in one or more programming languages (e.g., C or C++).

Preferred qualifications:

• Master's or Phd degree in Computer Science or Electrical Engineering, or a related field.
• 1 year of relevant industry experience.
• Experience in silicon image signal processing (ISP) programming in an embedded environment.
• Experience in image processing, computer vision, and computational photography development.
• Experience in GPU/DSP/TPU programming and optimization.

About the job

We are a team that is passionate about building the world's best mobile camera solutions to our users, partnering with teams across Google.We work with multiple teams to provide the best camera quality and experiences.

As part of the ISP IQ software team, you will have to work with global talents to launch scalable and efficient software and hardware Image Signal Processing solutions (ISP) and ensure the best mobile Image Quality (IQ) for Pixel Camera. You will develop camera solutions which will involve Android software, silicon camera ISP, image quality design, imaging algorithm performance evaluation and feature development.
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.

Responsibilities

• Design and development of imaging signal processing (ISP) image quality tuning infrastructure and automatic validation methods.
• Pixel camera system software performance, power, and memory optimization.
• Contribute to implementation and optimization of computer vision algorithms running on embedded hardware.
• Machine learning and computer vision algorithm development, integration and optimization running on embedded hardware, such as CPU/GPU/TPU/DSP/ISP .
• Collaborate with multiple teams (such as gChip/TechEng Hardware/Software, Pixel Algorithm/Software/Image Quality, Research, Android Camera HAL/Software team, etc.) to discuss requirements, interfaces, algorithm integration, and develop solutions to achieve quality goals and commercialize actual products.