> Markdown version of [/jobs/ext/1437450-software-engineer-on-device-machine-learning](https://www.wearedevelopers.com/jobs/ext/1437450-software-engineer-on-device-machine-learning). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, On-Device Machine Learning - **Company:** Google LLC - **Location:** Sunnyvale, CA, United States - **Experience:** Experienced - **Salary:** $147,000.0 - $211,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Android Software Development, Apple IOS, Mobile Application Development, Software Debugging, Distributed Systems, Design of User Interfaces, High-Level Architecture, Web Browsers, Push Technology, Information Retrieval, Machine Learning, Natural Language Processing, Performance Tuning, Tensorflow, Software Engineering, Systems Architecture, Data Processing, Data Storage Technologies, Pytorch, Model Validation, Generative AI, Information Technology, Search Engines, Hardware Acceleration, Machine Learning Operations, Programming Languages - **Published:** July 25, 2026 - **Apply:** https://dejobs.org/x/x/745C251B414949B1BCD9B0BD36EB7AF7/job/ ## About the Role Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area., * 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. * 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). * Experience with runtimes and performance tuning. * Experience in mobile development. Preferred qualifications: * Master's degree or PhD in Computer Science or related technical fields. * Experience in leading and delivering successful 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). * Strong understanding of Generative AI model architectures and their optimization for on-device execution. * Passion for innovation and a strong desire to push the boundaries of what's possible with on-device ML. ## 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., * Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). * Implement solutions in one or more specialized ML areas, utilize ML infrastructure, and contribute to model optimization and data processing. * Develop LiteRT, Google's on-device AI framework for first- and third-party, enabling SOTA hardware acceleration and use cases on edge platforms. * Enable on-device deployment of key models, such as Gemini Nano and Gemma, across various accelerators (GPU/Pixel TPU/NPUs/CPU) on Android, Chrome, iOS, desktop, 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) - [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) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Developing an AI.SDK](https://www.wearedevelopers.com/videos/198-developing-an-ai-sdk) - [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) ## 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) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)