Senior Staff Software Engineer, Agentic AI for XR

In most instances, this position requires in-person interviews as part of the hiring process.

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

Minimum qualifications:

• 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 optimizing end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with one or more of the following: on-device models (LLMs and multimodal models) and Multimodal AI agents, including architecting systemic solutions for strict mobile and wearable system constraints (memory/RAM limits, thermal envelopes, battery/power budgets, real-time latency, and Android/iOS background execution lifecycles).

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 8 years of experience with data structures and algorithms.
• Expertise across mobile and on-device ML runtimes, compilers, and frameworks (e.g., LiteRT/TFLite, AICore, MediaPipe, CoreML, hardware accelerators/NPUs, or cross-platform C++ runtimes).
• Track record directing organization-wide model and agent hillclimbing (e.g., model co-design, distillation, quantization, LoRA, prompt/System Instruction architecture, synthetic data ecosystems) and systematic AI quality and performance hillclimbing.
• Ability to align multi-year technical strategy and execution across executive leadership in mobile platform (Android/iOS), research (GDM), silicon/hardware, infrastructure, and product management.

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.

Our team is at the forefront of building the next generation of wearable conversational AI. We are developing multimodal, agentic AI solutions across various XR devices, utilizing Gemini to create a unique, proactive, and trusted multimodal experience. By combining on-device intelligence with cloud-scale reasoning, this technology delivers instant, natural conversational and agentic intelligence directly to the user's eye, ear, and mobile device - operating seamlessly within real-world mobile and wearable system constraints. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits

Learn more about benefits at Google.

• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
• Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of solutions across multiple specialized ML areas.
• Set the organization-wide technical direction and architectural standards for integrating, co-designing, and optimizing on-device Large Language Models (LLMs) and multimodal models across Android and iOS platforms.
• Define and execute the end-to-end strategy for data curation, automated evaluation, System Instructions (SI), agent configuration, model quantization/adaptation, and post-training of Gemini and on-device models across critical mobile and smart glasses use cases - jointly optimizing task quality and system efficiency (latency, memory, and battery).

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Jose, CA, USA; San Francisco, CA, USA.