Senior Software Engineer, AI Core Capabilities

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.

This role is ideal for those who are enthusiastic about delivering groundbreaking mobile experience changes by leveraging AI technology within the Android ecosystem.

The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.

Responsibilities

• Collaborate closely with DeepMind, CoreML, and Research to adapt and implement the Gemini Nano model for mobile user applications.
• Build simple, solid, and impactful developer-facing ML Kit and AICore APIs to empower both first-party and third-party app developers to create innovative user experiences with GenAI technologies in Android applications.
• Optimize the on-device inference latency and resource consumption for various Gemini Nano versions (V1, V2, V3, V4, etc.), ensuring they are optimally integrated into the mobile environment across the Android ecosystem.
• Work closely with product teams to innovate and implement novel user experiences and agentic workflows, leveraging techniques like Functional Calling, Retrieval-Augmented Generation (RAG), constraint decoding, gemma embedding, multi-modal processing, traditional machine learning models, LoRAs, and targeted Large Language Model (LLM) fine-tuning.