Senior Staff Software Engineer, On-Device Machine Learning
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with design and architecture and testing or launching software products.
Preferred qualifications:
- Experience in leading and delivering ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices).
- Experience in ML frameworks, e.g., PyTorch, JAX, TensorFlow.
- Experience with on-device ML SDKs/tooling, (e.g., TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN).
- Knowledge of ML converters/compilers and run times, and hardware-accelerated ML inference techniques.
- Understanding of Generative AI model architectures and their optimization for on-device execution.
- Passion for innovation and to advance what's possible with on-device ML.
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.
The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the latest advancements in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.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 and guide critical projects in Google's on-device ML infrastructure.
- Enable on-device deployment of key models, across various accelerators (GPU/Pixel TPU/NPUs/CPU) on Android, Chrome, and more.
- Improve performance of on-device model inference via optimizations in the model structure, on-device runtime and kernel implementation.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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