Staff AI Engineer, Multimodal Agentic AI for Glasses
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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: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with design and architecture; and testing/launching software products.
- Experience with Generative AI.
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.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience with Multimodal Machine Learning.
- Experience with large-scale infrastructure.
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.
Our team is at the forefront of building the next generation of conversational AI. We are developing multimodal, agentic AI solutions for smart glasses to create a unique, proactive, and trusted multimodal experience. This technology delivers instant, natural conversational intelligence directly to the user's eye and ear, allowing them to navigate and interact with their physical world more immersively than ever.
breakthroughs in compute, connectivity, mobile, and now, AI. Google's XR
team is at the forefront of the next major leap – the convergence of AI and XR. This is more than just new devices – it's about reimagining how we interact with the world around us. We're building a future where
lightweight XR devices like smart glasses and headsets pair with helpful AI to augment human intelligence, offering personalized, conversational, and contextually aware experiences.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead our most complex, ambiguous, and high-impact AI initiatives, taking foundational capabilities from early research and architectural definition through flagship production launches.
- Own the multi-quarter technical strategy, system architecture, and end-to-end quality across multiple core pillars, driving model and agent quality improvement through data strategy, evaluation frameworks, system prompting, skill and tool use, Agent harness, and model post-training to deliver an instant, natural, and immersive experience for users at scale.
- Architect and scale multi-turn, goal-oriented agentic workflows for real-world task assistance, featuring fact-grounded sourcing, plan decomposition, persistent context tracking, and multi-session continuity.
- Define and execute the end-to-end strategy for data curation, automated evaluation, system prompting, agent configuration, and post-training of Gemini models across critical smart glasses use cases—including real-time visual grounding, spatial and contextual state reasoning, and proactive multimodal interaction.
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