Embedded Software Engineer, Machine Learning Runtime, Silicon - Google
Mountain View, CA
About the Job
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience working with embedded operating systems.
- 2 years of experience with software development in one or more programming languages (e.g., C++), or 1 year of experience with an advanced degree.
- 1 year of experience with software frameworks for mobile ML or graphics (e.g., TFLite, Vulkan, OpenCL, CUDA, etc.).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience with machine learning algorithms and computer architecture.
- Experience working with hardware and machine learning accelerators.
- Experience with on-device machine learning, and knowledge of NLP, image, and on-device Generative AI.
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.
We are the team that builds Google Tensor, a custom System-on-Chip (SoC) that powers the latest Pixel phones. Tensor makes transformative user experiences possible with the help of Machine Learning (ML) running on Tensor TPU. The goal is to productize the latest ML innovations and research by delivering computing hardware and software.As a Software Engineer you will work on the mobile software stack for the Tensor SoC, with a focus on deployment of on-device ML framework for a range of user experiences including Camera, Speech, Generative AI, and more. You will be responsible for managing project priorities, deadlines, and deliverables.
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.
The US base salary range for this full-time position is $136,000-$200,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
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
- Develop on-device Runtime software stack to deploy ML models on mobile devices.
- Track and drive performance and power optimizations to enable on-device models.
- Support customers with deploying their ML models to the Tensor TPU.
- Work with application software teams to prototype and enable new use cases on Tensor SoCs.
- Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on software, hardware, and quality.
