XR System Performance Engineer - Optimize Glasses OS

Socket.dev; San Jose (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google is seeking a skilled XR System Performance Engineer to optimize the AR Glasses OS stack, focusing on end-to-end performance under strict latency and power constraints. You will analyze workloads from API calls to microXR architecture and drive architecture decisions.

You will mentor peers, write impactful code, and help shape the system's performance benchmarks and profiling methodologies for a next‑gen wearable platform powered by AI.

Qualifications

• 8 years of software development experience in C++ or Java.
• 5 years testing and launching software products.
• 5 years of performance, large-scale systems analysis, or debugging.
• 3 years of software design and architecture.
• 8 years of data structures and algorithms.
• Experience in technical leadership and cross-functional projects.
• Familiarity with system performance benchmarks and profiling tools.

Responsibilities

• Architect and vet system designs with a focus on end-to-end performance optimizations.
• Analyze performance of workloads from high-level APIs to low-level architecture.
• Communicate decisions via architecture documents and code.
• Mentor team members on architecture, coding standards, and debugging complex interactions.
• Review code and contribute to productivity through workflow improvements.

Skills

C++/Java

Testing & launching software

Performance analysis

Software design & architecture

Data structures & algorithms

Technical leadership

Cross-functional collaboration

Performance profiling tools

Education

Bachelor's degree or equivalent

Master’s degree in Engineering/CS

Job description

Google is seeking a skilled XR System Performance Engineer to optimize the AR Glasses OS stack, focusing on end-to-end performance under strict latency and power constraints. You will analyze workloads from API calls to microXR architecture and drive architecture decisions.

You will mentor peers, write impactful code, and help shape the system's performance benchmarks and profiling methodologies for a next‑gen wearable platform powered by AI.