XR Multimodal AI Engineer – On-Device & LLM Innovator

Google; New York (NY); On-site; USD 147,000 - 210,000; Full time

Benefits offered by this job

Equity

Bonus

Benefits

Job summary

Google is seeking a software engineer focused on advancing multimodal and conversational AI for next‑gen wearable XR devices. You will work on large language models and agents, emphasizing vision and audio, to build capable AI for glasses and headsets.

The role involves collaborating with XR product teams, researchers, and engineers to push the frontier of AI research and product integration, while maintaining power and latency constraints on devices.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year with an advanced degree.
• 1 year of experience with speech/audio, reinforcement learning, ML infrastructure, or related ML field.
• 1 year of experience with ML frameworks such as JAX, TensorFlow, or PyTorch.

Responsibilities

• Lead development and optimization of on-device and hybrid multimodal models for XR devices.
• Create evaluation plans for hybrid systems and define KPIs for model accuracy and efficiency.
• Identify and ship the latest modeling innovations with hybrid agent architectures and edge-cloud orchestration.
• Prototype on-device AI features and work closely with XR product teams for testing and launches.
• Collaborate with researchers and engineers to drive the technical roadmap and share findings.

Skills

Programming languages

ML frameworks

Speech/Audio

Multimodal learning

On-device model optimization

Education

Bachelor's degree

Master's or PhD (preferred)

Tools

JAX

TensorFlow

PyTorch

Job description

Google is seeking a software engineer focused on advancing multimodal and conversational AI for next‑gen wearable XR devices. You will work on large language models and agents, emphasizing vision and audio, to build capable AI for glasses and headsets.

The role involves collaborating with XR product teams, researchers, and engineers to push the frontier of AI research and product integration, while maintaining power and latency constraints on devices.