Staff Systems Engineer - AV Sensing Design

Job Description General Motors is developing hands-off and eyes-off autonomous driving systems intended for broad deployment across consumer vehicles. As part of this effort, GM is investing in sensors and architectures that can be integrated, validated, and operated reliably at scale across diverse vehicle programs and operating environments. Job Description General Motors is developing hands-off and eyes-off autonomous driving systems intended for broad deployment across consumer vehicles. As part of this effort, GM is investing in sensors and architectures that can be integrated, validated, and operated reliably at scale across diverse vehicle programs and operating environments. We are seeking a staff systems engineer to join the AV team to provide technical leadership in defining how autonomous sensing systems are architected and integrated across GM’s autonomy programs. This role focuses on sensor suite design at the intersection of sensors, Perception, Behaviors, and vehicle integration, ensuring that sensing solutions are technically sound, aligned with product intent, and executable in production. In this position, you will apply your specific areas of expertise to develop solutions to novel challenges as you lead system‑level trade studies, perform detailed analysis on individual sensors, and define multi-modality sensor suites spanning camera, radar, lidar, and more. You will work closely with AI/ML, simulation, data collection, platform software, and vehicle integration teams to address real engineering challenges. This role is for engineers who thrive in navigating ambiguous problem spaces and bring clarity to cross-functional teams with data-driven solutions. What You’ll Do Lead system level trade studies for the design of multi-modality sensor systems supported by detailed modeling of performance and AV behavioral impacts Develop detailed performance specifications for sensors supported by a strong understanding of sensor physics and signal processing Assess performance against product needs to assess risk, quantify impact, and drive continuous improvement Work closely with cross-functional stakeholders such as simulation, vehicle integration, perception, localization, and validation teams to manage complex interdependencies Clearly document technical decisions, trade‑offs, and deliverables. Your Skills & Abilities (Required Qualifications) Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical discipline 10+ years of experience with B.S. with significant sensor related experience Demonstrated leadership experience executing cross-functional initiatives across system architecture, data collection, analysis, integration, or other related activity Experience developing multi-modality sensing systems (camera, radar, lidar, or similar), their definition, usage, and integration Technical depth in signal processing, link analysis, or ML across at least one relevant sensing modality Understand the challenges of self-driving and how those map to sensor needs Demonstrated ability to operate effectively in ambiguous problem spaces and drive technical alignment across teams Strong written and verbal communication skills and the ability to communicate detailed technical information Working knowledge of Matlab, Python, or other languages to support data analysis and analysis tooling development What Will Give You a Competitive Edge (Preferred Qualifications) Master’s or PhD degree in engineering or a related technical discipline Experience developing systems for occupantless self-driving autonomous vehicles or advanced remote sensing platforms Significant experience with automotive autonomy focused SPAD lidars and/or imaging radar data and failure modes Experience developing and leading system/component validation strategy, including use case definition, test protocol development, vehicle testing, HIL/SIL, simulation, and/or large‑scale data analysis Experience analyzing extrinsic calibration, pointing accuracy tolerance stacks, and similar concepts Autonomous vehicle behavior modeling and assessment Experience with sensor simulation model development Compensation The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington. The salary range for this role is 189,300 to 290,700. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. Relocation benefits are available for candidates who qualify under company policy. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources . 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