XR Embedded Systems Engineer — Edge AI & Sensing

Socket.dev; San Jose (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google's XR team is building the next leap in AI-powered wearables, edge sensing, and real-time ML applications. We seek software engineers to architect embedded systems, develop firmware and drivers, and collaborate with ML teams to deploy sensing solutions at scale.

You will contribute to power, latency, and memory optimizations on intelligent edge devices. Responsibilities include prototyping new edge features, integrating sensors, and translating system designs into robust firmware across

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years of experience with software development in C/C++.
• Experience designing and architecting embedded systems including MCUs, RTOS, memories, interfaces and sensors.
• Firmware and driver development for embedded systems.
• Experience with low-power AI processors, sensor solutions, and system architecture.
• Master's degree or PhD in CS or related field.
• 5 years of experience with data structures and algorithms.
• Distributed ML and ML infrastructure experience.
• Experience training and optimizing deep learning models.

Responsibilities

• Architect and develop embedded systems for intelligent edge sensing applications.
• Develop firmware and drivers for embedded systems.
• Collaborate with ML engineers to implement real-time ML sensing applications.
• Optimize embedded ML model performance for power, latency, and memory.
• Create prototypes to demonstrate new edge sensing features.

Skills

5 years of experience with C/C++

Embedded systems design

Firmware & driver development

Low-power AI processors and sensors

I2C, SPI, UART, MIPI, CSI2, I3C, BLE

Education

Bachelor's degree in CS/EE

Master's or PhD in CS or related field

Tools

Python

Job description

Google's XR team is building the next leap in AI-powered wearables, edge sensing, and real-time ML applications. We seek software engineers to architect embedded systems, develop firmware and drivers, and collaborate with ML teams to deploy sensing solutions at scale.

You will contribute to power, latency, and memory optimizations on intelligent edge devices. Responsibilities include prototyping new edge features, integrating sensors, and translating system designs into robust firmware across