Camera Software Engineer, Pixel

Minimum qualifications:

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

Preferred qualifications:

• Master's degree or PhD in Computer Science, Electrical Engineering, or a related field.
• 10 years of experience in engineering.
• Experience in silicon Image Signal Processing (ISP) programming and 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're a team that's passionate about building mobile camera solutions to delight our users, partnering with teams across Google.

As part of the ISP IQ Software team, you'll have the chance to work with global talents to launch scalable and efficient software and hardware ISP (Image Signal Processing) solutions and ensure the best mobile IQ (Image Quality) for Pixel Camera.

In this role, you will develop Camera solutions which will involve Android software, silicon camera ISP, image quality design, imaging algorithm performance evaluation and feature development. We work with multiple teams to provide the best camera quality and experiences.

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 develop Imaging Signal Processing (ISP) image quality tuning infra and automatic validation methods.
• Oversee Pixel camera system software performance, power, and memory optimization.
• Contribute to the implementation and optimization of computer vision algorithms running on embedded hardware.
• Work on machine learning and computer vision algorithm development, integration and optimization running on embedded hardware, such as CPU/GPU/TPU/DSP/ISP.
• Lead/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.