AI Software Engineer, Multimodal Agentic AI for Glasses

AI Software Engineer, Multimodal Agentic AI for Glasses

corporate_fareGoogleplaceSan Jose, CA, USA

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 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.
• 3 years of experience with end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
• Experience with Generative AI.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• 5 years of experience with data structures/algorithms.
• 1 year of experience in a technical leadership role.
• 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.
As a Senior AI Engineer, you will play a technical leadership role at the forefront of developing groundbreaking multimodal agentic AI solutions for smart glasses. You will architect and ship trusted, real-time conversational experiences that seamlessly blend voice, streaming vision, and physical-world context.

For decades, the computing revolution has reshaped our world driven by
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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.

Responsibilities

• Play a technical leadership role at the forefront of developing groundbreaking multimodal agentic AI solutions for smart glasses.
• Take ambitious, ambiguous AI capabilities from initial research and rapid prototyping to flagship production launches.
• Own the end-to-end technical direction and quality of core pillars, driving model and agent quality improvement through data optimization, evaluation benchmarks, system prompting, skill and tool use, Agent harness, and model post-training to deliver an instant, natural, and immersive experience for users.