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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Staff Software Engineer, AI Edge - **Company:** Google LLC - **Location:** Sunnyvale, CA, United States - **Experience:** Expert - **Salary:** $262,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Android Software Development, Apple IOS, C++ (Programming Language), Compilers, Software Debugging, Distributed Systems, Design of User Interfaces, Web Browsers, Push Technology, Information Retrieval, Machine Learning, Natural Language Processing, Tensorflow, Software Engineering, Systems Architecture, Data Processing, Data Storage Technologies, Model Validation, Gpu Programming, Information Technology, Search Engines, Machine Learning Operations - **Published:** September 8, 2026 - **Apply:** https://dejobs.org/x/x/3604E999AECD4A579927067336706CDF/job/ ## About the Role Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain., * 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 design and architecture; and testing/launching software products. * Experience with machine learning infrastructure, C++, performance, GPU programming, mobile GPU., * Master's degree or PhD in Engineering, Computer Science, or a related technical field. * Experience with on-device ML Software Development Kits (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. * Strong 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). ## Description 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., * Train task-specific models of in app AI (tiny Gemma/Juno Nano), enabling Gemma model/runtime co-design (quantization, conversion), build industry-leading on-device AI solutions (voice translate, generative image editing). * Enable developers to test/evaluate/deploy across devices (Edge Portal /Model Explorer/Developer Device Platform). * Develop and guide critical projects in Google's on-device ML infrastructure (e.g., LiteRT, LiteRT-LM). * 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. ## Related Videos - [Xcode development redefAIned](https://www.wearedevelopers.com/videos/100195-xcode-development-redefained) - [Just-in-time Compilation in JVM](https://www.wearedevelopers.com/videos/240-just-in-time-compilation-in-jvm) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Future of Mobile AI. What On-Device Intelligence Means for App Developers](https://www.wearedevelopers.com/videos/100264-future-of-mobile-ai-what-on-device-intelligence-means-for-app-developers) - [Edge AI on iOS: Beyond the Cloud, Designing the Next Generation of Intelligent On-Device Apps](https://www.wearedevelopers.com/videos/100225-edge-ai-on-ios-beyond-the-cloud-designing-the-next-generation-of-intelligent-on-device-apps) - [Harnessing Apple Intelligence: Live Coding with Swift for iOS](https://www.wearedevelopers.com/videos/1515-harnessing-apple-intelligence-live-coding-with-swift-for-ios) ## Related Articles - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)