Staff Sensor Systems Engineer

Date PostedMay 13, 2026LocationHybrid/Remote (within 50 miles of a GM Technical center)CompanyGeneral MotorsSalary$189,300- $290,700TypeSenior Level

Job Summary

General Motors is seeking a Staff Systems Engineer to lead the architecture and integration of autonomous sensing systems, including camera, radar, and lidar. This role involves defining system-level requirements, driving cross-domain technical alignment, and ensuring sensing solutions are robust and production-ready. The candidate will work at the intersection of embedded software, vehicle platforms, and autonomy software to address complex engineering challenges.

Responsibilities

  • Lead autonomous sensor system trade studies and architecture.
  • Decompose system requirements for camera, radar, and lidar.
  • Coordinate cross-functional teams (perception, software, hardware).
  • Ensure compliance with safety and regulatory standards.

Required Skills

  • 10+ years in systems engineering/integration.
  • Expertise in sensor modalities (Camera/Radar/Lidar).
  • Proficiency in Matlab/Python for analysis.
  • Strong technical leadership and requirements management.

Job Details

### Position Overview General Motors is developing hands-off and eyes-off autonomous driving systems intended for broad deployment across consumer vehicles. This role focuses on system-level decisions at the intersection of sensors, embedded software, vehicle platforms, and autonomy software, ensuring that sensing solutions are technically sound, aligned with product intent, and executable in production. ### Key Responsibilities - Lead system-level trade studies, define sensor systems spanning camera, radar, and lidar, and work closely with perception, platform software, and vehicle integration teams. - Lead system-level trades, requirement decomposition, definition, and integration of autonomous sensor systems. - Provide detailed technical analysis from component level to system for autonomous vehicle sensing functions across performance, latency, data integrity, synchronization, and hardware/software interaction. - Translate autonomy and product intent into system architectures, functional decompositions, and requirements. - Collaborate with software platform, vehicle integration, hardware, perception, and validation teams to manage complex interdependencies. - Ensure system designs meet safety, regulatory, quality, and performance requirements relevant to autonomous vehicle operation. - Drive continuous improvement in sensing system performance, robustness, diagnostics, integration, and cost. - Clearly document technical decisions, trade-offs, and deliverables. ### Required Qualifications - Bachelor's degree in Systems, Electrical, Software, Mechanical Engineering, or equivalent work experience. - 10+ years of experience in systems engineering, system integration, or hardware-intensive product development. - Experience working with sensing systems (camera, radar, lidar) and their integration into vehicles. - Experience leading system architecture, integration, and cross-domain technical initiatives. - Strong expertise in requirements development, interface definition, integration, and validation. - Technical depth in signal processing, link analysis, or ML across at least one relevant sensing modality. - Demonstrated ability to operate effectively in ambiguous problem spaces. - Proficiency with Matlab, Python, or other languages for data analysis and tool development. ### Preferred Qualifications - Master's degree in Engineering or a related technical discipline. - Experience with L4 autonomous vehicle programs or advanced remote sensing platforms. - Experience developing, debugging, or integrating embedded or systems-level software. - Significant experience with automotive autonomy-focused SPAD lidars and/or imaging radars. - Experience with requirements management tools such as JAMA or DNG. - Knowledge of safety-critical system development or functional safety concepts. - Experience with system/component validation, including vehicle testing, HIL/SIL, simulation, and large-scale data analysis.