Principal M-LLM Post-Training & Execution Lead

Google; San Jose (CA); On-site; USD 307,000 - 427,000; Full time

Job summary

Google is seeking a Principal Software Engineer for Multimodal LLM post-training and execution to drive production-ready features for the XR platform. You will balance state-of-the-art model alignment with high-performance real-time execution on XR devices.

Lead large-scale CV and multimodal data pipelines, collaborate with product and UX teams, and shape the next generation of spatial computing experiences while ensuring safety and reliability.

Qualifications

• Bachelor’s degree in Computer Science, Mathematics, or equivalent practical experience.
• 15 years of experience in software engineering, specifically in large-scale machine learning systems or computing.
• Experience driving the go-to-market strategy for AI-driven technologies.
• Experience leading engineering teams through the full execution cycle of AI products.

Responsibilities

• Design and scale the post-training infrastructure for Multimodal LLMs, including instruction tuning, RLHF, and automated evaluation frameworks.
• Architect and optimize the execution engines that support real-time M-LLM inference on XR hardware, balancing high-fidelity output with battery-conscious processing.
• Lead the development of large-scale computer vision and multimodal data pipelines to improve model understanding of spatial and environmental contexts.
• Partner with Product and UX teams to define the "intelligence" primitives that will power the next generation of spatial applications.
• Set the standard for model safety and alignment for XR-specific use cases, ensuring responsible AI deployment at scale.

Skills

Software engineering

Go-to-market strategy

Leadership

Multimodal AI

Real-time XR

Education

Bachelor’s degree in Computer Science or Mathematics

Job description

Google is seeking a Principal Software Engineer for Multimodal LLM post-training and execution to drive production-ready features for the XR platform. You will balance state-of-the-art model alignment with high-performance real-time execution on XR devices.

Lead large-scale CV and multimodal data pipelines, collaborate with product and UX teams, and shape the next generation of spatial computing experiences while ensuring safety and reliability.