Principal M-LLM Post-Training and Execution Software Engineer, XR

About the role

MINIMUM 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.

PREFERRED QUALIFICATIONS:

• Experience with high-performance inference engines and custom AI

accelerators.

• Advanced knowledge of computer vision pipelines, 3D perception, and their

integration with large-scale language models.

• Distinctive problem-solving and analytical skills applied to the challenges

of real-time spatial computing.

• Specialized expertise in large-scale post-training workflows, including

Reinforcement Learning from Human Feedback (RLHF) and fine-tuning at scale.

ABOUT THE JOB:

At Google, we put our users first, and the Android XR team is building the

future of how users experience the world through augmented and virtual reality.

As the Principal SWE for Multimodal LLM (M-LLM) Post-Training & Execution, you

will lead the critical efforts to take state-of-the-art research models and

transform them into production-ready features for the XR platform. This role is

uniquely positioned at the intersection of model alignment and high-performance

execution. You will ensure our models are not only intelligent but also safe,

reliable, and optimized for the real-time demands of XR environments. Your work

will empower XR devices to "see" and "understand" the world in ways never before

possible.

The Platforms and Devices team encompasses Google's various computing software

platforms across environments (desktop, mobile, applications), as well as our

first party devices and services that combine the best of Google AI, software,

and hardware. Teams across this area research, design, and develop new

technologies to make our user's interaction with computing faster and more

seamless, building innovative experiences for our users around the world.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

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.