Software Engineer, On Device Machine Learning

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Science, a relevant technical field, or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages (e.g., C++/C, Java, Python, JavaScript).
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, model serving, data processing, debugging, fine tuning) or agentic AI development.

Preferred qualifications:

• Experience in building Android machine learning infrastructures and applications.
• Experience in Android development.
• Solid knowledge of advanced AI models (e.g., LLM) design/implementation and their application to real-world problems.
• Understanding of on-device ML technologies such as quantization and hardware acceleration.
• Familiarity with operating systems.

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.

In this role, you will be able to get in touch with the latest models from DeepMind and CoreML, explore novel techniques for On-Device Machine Learning (ODML), work closely with various AI/ML teams and collaborate with a strong cross-functional group of Engineering/Product Management/UX across the platform and ecosystem product area.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

Responsibilities

• Adapt models (e.g., computational graph, quantization) for accurate and efficient execution on hardware accelerators (GPU/NPU).
• Create end-to-end model serving infrastructures for different applications needs and design AI-powered user-facing features and build app surfaces that deliver them.
• Orchestrate quality tests and benchmark performance across a wide variety of models including embedding, Large Language Model (LLM), image inference and image generation.
• Customize models for optimal performance in specific domains (e.g., LoRA training).
• Provide technical underpinning for production launches such as i18n, provenance and Trust and Safety.