Staff Systems Engineer: Autonomous Sensing & Integration

General Motors LLC; Sunnyvale (CA); Hybrid; USD 189,000 - 291,000; Full time

Benefits offered by this job

Relocation benefits

Hybrid work model

GM benefits package

Job summary

General Motors LLC seeks a Staff Systems Engineer to lead sensor system design for autonomous driving programs. You'll define multi-modality sensor suites, trade studies, and performance specs across camera, radar, lidar, and more, collaborating with AI/ML, simulation, data collection, and vehicle teams.

You'll drive technical alignment, document decisions, and shape production-ready architectures while operating in a hybrid environment at GM.

Qualifications

• Bachelor’s degree in Electrical/Computer Engineering or Computer Science.
• 10+ years of sensor-related experience with leadership in cross-functional initiatives.
• Experience developing multi-modality sensing systems (camera, radar, lidar).
• Depth in signal processing, link analysis, or ML for at least one sensing modality.
• Strong communication and ability to operate in ambiguous spaces.

Responsibilities

• Lead system level trade studies for multi-modality sensor designs.
• Develop performance specs for sensors based on physics and signal processing.
• Assess sensor performance vs product needs and drive improvements.
• Collaborate with simulation, vehicle integration, perception, and validation teams.
• Document technical decisions, trade-offs, and deliverables.

Education

Bachelor’s degree in Electrical Engineering

Bachelor’s degree in Computer Engineering

Bachelor’s degree in Computer Science

Master’s or PhD degree (preferred)

Tools

MATLAB

Python

Job description

General Motors LLC seeks a Staff Systems Engineer to lead sensor system design for autonomous driving programs. You'll define multi-modality sensor suites, trade studies, and performance specs across camera, radar, lidar, and more, collaborating with AI/ML, simulation, data collection, and vehicle teams.

You'll drive technical alignment, document decisions, and shape production-ready architectures while operating in a hybrid environment at GM.