Software Engineer, Machine Learning Runtime, Silicon
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
- 2 years of experience working with embedded operating systems.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- Experience working with hardware and ML accelerators (e.g., experience at a company that builds ML chips).
- Experience with machine learning algorithms and computer architecture.
- Experience with on-device ML (e.g., an understanding of NLP, image and vision, on-device GenAI).
About the job
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.
Silicon Compute Software (SW) organization focuses on software and ML technology for the Camera, Speech and Ambient Experiences on Pixel devices. As a Software Engineer, you will work on the mobile SW stack for the Tensor SoC, with a focus on deployment of on-device ML framework for a range of user experiences including Camera, Speech, GenAI, etc. Along with your technical expertise, you will manage project priorities, deadlines and deliverables.
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
- Develop on-device Runtime SW stack to deploy ML models on mobile devices.
- Track and drive performance and power optimizations to enable large on-device models.
- Support customers with quickly deploying their ML models to the Tensor TPU.
- Work with application software teams to prototype and enable new use cases on Tensor SoCs, while also participating in, or leading technical design reviews with peers and stakeholders.
- Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency) and triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on SW, Hardware (HW) and quality.
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