Staff Systems Engineer – Sensor Systems Engineering & Architecture
General Motors
- Location
- Sunnyvale, California, United States of America
- Work model
- On-Site
- Level
- Staff
- H-1B history
- 267 approvals (FY2023)
- Posted
- Aug 28, 2026
Skills
About this role
Job Description
General Motors is developing hands-off and eyes-off autonomous driving systems intended for broad deployment across consumer vehicles. A foundational requirement for safe, scalable autonomy is that sensing systems perform reliably across the full range of real-world weather conditions. We are seeking a Staff Systems Engineer to join the Sensor Systems Engineering & Architecture team to provide technical leadership in defining how autonomous sensing systems are characterized, specified, and validated under weather and contamination conditions. This role focuses on system-level decisions at the intersection of sensors, perception software, vehicle platforms, and real-world operating environments — ensuring that sensing solutions are technically sound, weather-resilient, and executable in production. In this position, you will lead system-level trade studies, define performance requirements for sensors under adverse weather and contamination scenarios, and develop the technical frameworks used to assess sensor cleaning solutions. You will work closely with perception , validation, platform software, and vehicle integration teams to drive forward a rigorous and scalable approach to weather and cleaning performance assessment. This role is intended for engineers who are comfortable operating in ambiguity, applying first-principles analysis, and providing steady technical direction as systems mature from early development into deployed solutions. What You’ll Do You will get the op portunity to contribute to one or more of the following. Lead system-level trades, requirements decomposition, and integration requirements for autonomous sensor systems across radar, cameras, and lidar with associated cleaning systems Lead the technical assessment, characterization, and performance benchmarking of sensor systems — including active and passive cleaning mechanisms — across vehicle programs Translate autonomy and product performance intent into system architectures, functional decompositions, and requirements Work closely with software platform teams, vehicle integration, hardware teams, perception, and validation teams to manage complex interdependencies and drive forward progress Ensure system designs meet safety, regulatory, quality, and performance requirements relevant to autonomous vehicle operation in diverse environmental conditions Drive continuous improvement in sensing system robustness Clearly document technical decisions, trade-offs, and deliverables. Your Skills & Abilities (Required Qualifications) Bachelor's degree in Systems, Electrical, Software, Mechanical Engineering, or a related technical field 10+ years of experience in systems engineering, system integration, or hardware-intensive product development Experience working with sensing systems (camera, radar, lidar, or similar) and a technical understanding of the effects of weather and contamination on performance Experience leading cross-domain technical initiatives for the evaluation and validation of sensor performance Expertise in requirements decomposition and development Demonstrated ability to operate effectively in ambiguous problem spaces and drive technical alignment across teams Experience with Matlab, Python, or other tools to support data analysis and analysis tooling development What Will Give You a Competitive Edge (Preferred Qualifications) Master's degree or PhD in Engineering or a related technical discipline Direct experience characterizing or modeling sensor performance degradation in adverse weather conditions (rain, snow, fog, aerosol, or equivalent) for high-fidelity sensors Familiarity with weather simulation methodologies, physics-based sensor modeling, or environmental test chamber evaluation Experience with sensor cleaning systems, including nozzle, air, wiper, or other advanced methods Experience working on