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X 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.
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.
Minimum qualifications: - Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- Experience integrating generative AI tools or LLM interfaces into workflows.
- 5 years of experience with software engineering and large-scale or mobile/embedded ML/AI system architecture and development in C , Kotlin/Java, Swift/Objective-C, or Python.
- 5 years of experience with mobile and on-device ML runtimes and frameworks (e.g., LiteRT/TFLite, AICore, MediaPipe, CoreML or cross-platform C runtimes) and hybrid on-device/cloud orchestration.
Preferred qualifications: - Master's degree or PhD in Engineering, Computer Science, or a related technical field.
- Exceptional cross-organizational influence and communication skills, with a proven ability to align technical strategy and execution across mobile platform (Android/iOS), research (GDM), infrastructure, product management, and hardware/device engineering teams.
- Proven track record leading model and agent hillclimbing (e.g., SFT, RL, LoRA, quantization, prompt/System Instruction tuning, synthetic data generation) and systematic AI quality and performance hillclimbing (architecting automated evaluation frameworks, autoraters, on-device latency/power benchmarks, and end-to-end loss analysis pipelines).
- Demonstrated technical leadership setting technical strategy, architecting foundational systems, and leading multiple engineers or cross-functional teams to deliver complex, ambiguous mobile AI, on-device ML, or agentic initiatives from conception to large-scale production across Android or iOS.
About the jobOur 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.
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: $207000 - $300000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Define the long-term technical solution and lead the architecture, development, and production deployment of scalable, low-latency, multi-turn agentic AI systems across XR devices paired to Android and iOS.
- Drive the foundational evolution wearable AI and agentic tech stack.
- Establish the technical direction and lead the architecture for integrating and optimizing on-device LLMs and multimodal models across Android and iOS platforms.
- Pioneer, prototype, and productionize multimodal AI, agentic reasoning, device-native tool use, and OS/app integrations tailored to always-on streaming audio, video, and mobile context under strict latency and compute constraints.
- Serve as the principal technical point of contact and bridge across XR, Mobile (Android and iOS), On-Device ML (ODML), and GDM teams.
