Image Signal Processing Machine Learning Modeling Engineer
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Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
- 5 years of experience in silicon engineering.
- Experience in C or C++ or Python programming.
- Experience in AI/ML accelerator or model development.
Preferred qualifications:
- Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
- Experience in reference model development and silicon design trade-off.
About the job
Our Devices and Services team combines the best of Google AI, Software, and Hardware to create 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 and Services team is making people's lives better through technology.Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Create and deliver software architecture for Machine Learning (ML) accelerator.
- Implement, model, analyze and test ML accelerator.
- Develop the software environment for Image Signal Processing (ISP) ML accelerator development and simulation.
- Lead the delivery of ISP ML accelerator c-models for implementation, verification.
- Collaborate with partner teams to integrate the ML accelerator into compiler software environment.
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