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 with software development in one or more programming languages (e.g., Python, C, C++).
- 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 testing, and launching software products.
- Experience in performance analysis and optimization including GPU programming, mobile GPU, system architecture, performance modeling, benchmarking, machine learning infrastructure, or other similar experience.
- Experience with ML frameworks (e.g., PyTorch, JAX, TensorFlow).
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 5 years of experience in a technical leadership role leading project teams, setting technical direction, excellent communication, collaboration, working in a complex, matrixed organization.
- Experience with on-device ML SDKs/tooling (e.g., TensorFlow Lite, ExecuTorch, Core ML, SNPE/QNN).
- In-depth knowledge of ML converters/compilers and runtimes, and hardware-accelerated ML inference techniques.
- Understanding of Generative AI model architectures and their optimization for on-device execution.
- Proven track record of leading and delivering successful ML projects focused on on-device deployment (Android, iOS, web browsers, or embedded devices).
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.
Google AI Edge enables developers and Google products to deploy AI across mobile, web, and embedded with our AI edge stack - from low-code APIs to hardware specific acceleration libraries to achieve leading performance and device optionality at scale. Our team focuses on cross-platform infrastructure and solutions aligned with Google's biz needs: serving our Google Products across Android, iOS and Web, third-party developers, and building specialized solutions for Pixel.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $248,000-$349,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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 and guide critical projects in Google's on-device ML infrastructure (e.g., LiteRT, MediaPipe, GenAI Inference).
- Enable on-device deployment of key models, such as Gemini Nano and Gemma, 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 representation, on-device runtime, and kernel implementation.
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Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
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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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