ADAS Fusion Performance Engineer

Job Description As an ADAS Fusion Performance Engineer, you will be responsible for developing, optimizing, and validating object fusion performance for GM's Advanced Driver Assistance Systems (ADAS). This senior individual contributor position focuses on how radars, cameras, lidar, and other sensor modalities are fused and selected as relevant targets to deliver robust perception for safe, confident vehicle behavior across environments and use cases. You will collaborate closely with feature performance engineers, sensor performance engineers, system engineers, and software developers to ensure fusion outputs meet feature-level performance, safety, regulatory, and customer experience targets. Key Responsibilities Own fusion performance for assigned vehicle platforms from initiation through launch and field performance support. Lead vehicle and simulation testing to characterize and develop fusion performance, including test design, data collection, test execution, and results analysis for a wide range of environments, traffic scenarios, and edge cases. Develop and optimize fusion-related parameters utilizing big data, ensuring robust operation across vehicle lines and hardware variants, and delivering production-ready calibrations to programs on time. Serve as the single-point technical contact for fusion performance root cause and issue resolution, including correlation between sensor-level behavior and fused object/scene outputs. Collaborate with sensor performance engineers (radar, camera, lidar, etc.) to align sensor requirements and capabilities with fusion algorithm needs and feature performance targets. Use simulation and data‑driven methods (e.g., SIL/HIL, scenario-based testing, replay of recorded data) to evaluate, regress, and improve fusion algorithms and calibrations, complementing vehicle testing. Analyze complex data sets from on‑road vehicles, proving ground tests, and virtual environments to identify performance gaps, sensitivity to environmental factors, and opportunities for algorithm or calibration improvements. Support cross‑functional technical discussions and reviews with ADAS software, perception, planning, systems, program teams, safety, and validation to drive alignment on fusion performance decisions and trade‑offs. Support validation and verification activities for fusion-impacted features, such as Adaptive Cruise Control and Automatic Emergency Braking. Document and communicate results, lessons learned, and issues; contribute to standardized methods, tools, and metrics for fusion performance within the broader ADAS organization and program milestones. Travel as needed for development testing and performance buy‑offs at proving grounds and key test locations. Required Qualifications Bachelor of Science degree in Electrical Engineering, Mechanical Engineering, Computer Engineering, Computer Science, Systems Engineering, Robotics, or a related STEM discipline. Minimum of 5 years post‑graduate professional engineering experience, preferably in ADAS, automated driving, perception/fusion, or closely related fields. Demonstrated experience with vehicle or component/sensor development, integration, and diagnostics, including hands‑on test, data logging, and analysis. Strong understanding of sensor-based ADAS systems (e.g., radar, camera, lidar, ultrasonic, GNSS/IMU) and how they contribute to perception and feature behavior. Ability to root cause complex, multi‑domain problems involving sensors, perception/fusion algorithms, vehicle dynamics, and feature logic. Experience with complex vehicle instrumentation and data acquisition, including configuration of loggers and interpretation of time‑synchronized sensor and vehicle data. Familiarity with automotive communication networks such as CAN, GMLAN, and Ethernet, and associated tools for data inspection and debugging. Proficiency with engineering and data analysis tools commonly used in ADAS development (e.g., MATLAB/Simulink, Python, INCA/MDA, CAN tools such as Canalyzer or VSpy). Strong oral and written communication skills, with the ability to work effectively within multi‑disciplinary and cross‑functional teams, often under minimal direction. Valid driver's license and ability to operate test vehicles. Preferred Qualifications Master's degree in Electrical Engineering, Computer Engineering, Robotics, or related field with focus on perception, signal processing, or sensor fusion. 7+ years of overall engineering experience in automotive ADAS, robotics perception, or sensor fusion algorithm development and calibration. Direct experience in sensor fusion or perception algorithms (e.g., object detection, tracking, classification, multi-sensor association) and their calibration/performance tuning. Prior experience as an Active Safety or Automated Driving Performance Calibration Engineer, especially in areas such as Automatic Emergency Braking, Object Fusion, or Adaptive Cruise Control. Experience with virtual development and scenario-based testing, including SIL/HIL environments and large-scale data replay or synthetic data generation for ADAS performance evaluation. Knowledge of DFSS / Six Sigma methods and structured problem-solving; DFSS Black Belt or similar training is a plus. Understanding of global vehicle development processes and exposure to production release, launch, and field performance monitoring. Familiarity with regulatory and safety considerations for ADAS features (e.g., FMVSS requirements and emerging ADAS-related regulations) and their impact on fusion and perception performance. GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). 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}. The selected candidate will be required to travel