Embedded ML & Edge Firmware Engineer - Onsite Mountain View

Insight Global; Mountain View (CA); On-site; USD 79,000 - 98,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401k with employer matching

Paid time off

Job summary

Google in Mountain View, CA, seeks an Embedded Systems Engineer to design firmware for edge sensing devices and to collaborate with ML engineers on real-time ML sensing applications. The role emphasizes power and memory optimization and prototype development, with an onsite Mountain View requirement.

The candidate should have a strong background in embedded systems (C/C++, Python), MCU/RTOS design, and experience with ML in embedded contexts. Bachelor’s is required; Master’s/PhD is preferred.

Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience.
• 4 years of embedded systems experience or 3 years with an advanced degree.
• Experience developing ML-based image and voice embedded applications in C, C++, Python.
• Experience in designing embedded systems including MCUs, RTOS, memories, interfaces (I2C, SPI, UART, MIPI, CSI2, I3C, BLE) and sensors.

Responsibilities

• Architect and develop embedded systems for 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 usage.
• Create prototypes to demonstrate new edge sensing features.

Skills

Embedded systems

ML integration

Problem solving

Education

Bachelor’s degree in CS/EE or related

Master's or PhD (preferred)

Tools

C/C++

Python

RTOS

MCUs

Job description

Google in Mountain View, CA, seeks an Embedded Systems Engineer to design firmware for edge sensing devices and to collaborate with ML engineers on real-time ML sensing applications. The role emphasizes power and memory optimization and prototype development, with an onsite Mountain View requirement.

The candidate should have a strong background in embedded systems (C/C++, Python), MCU/RTOS design, and experience with ML in embedded contexts. Bachelor’s is required; Master’s/PhD is preferred.