Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
As a Software Engineer, you'll develop and deploy the prototype of the new Machine Learning model and applications for the next embedded device system.
Google's mission is to organize the world's information and make it universally accessible and useful. Our Hardware team researches, designs, and develops new technologies and hardware to make our user's interaction with computing faster, more powerful, and seamless. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, our Hardware team is making people's lives better through technology.
- Build tools that can map Machine Learning models to hardware.
- Evaluate various trade-offs of different optimization strategies such as performance, power, energy and memory consumption.
- Develop Machine Learning models to optimize hardware accelerators.
- Train Machine Learning models with lower complexity but achieving similar quality.
- Utilize the relevant system software stack needed to enable machine learning accelerator on a variety of Android and other Linux based devices.
- BS degree in Computer Science or related technical field, or equivalent practical experience.
- Experience with programming in C++.
- Experience with Machine Learning applied to imaging or computer vision.
- Experience in training new Machine Learning models for embedded system applications.
- Masters or similar advanced degree in Computer Science.
- Experience working with system software on embedded devices.
- Experience using Android/Brillo/Linux system software development and build systems.
- Experience with Linux Kernel device driver development and debugging.