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General Motors
General Motors
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General Motors is a global automotive and manufacturing company working across vehicle engineering, production, transportation, and information technology. Founded in 1908, GM develops technologies aimed at advancing mobility while pursuing its vision of zero crashes, zero emissions, and zero congestion. Its international operations bring together large, multidisciplinary teams focused on innovation, sustainable transportation, and the future of the automotive industry.
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Technical Lead Manager, Autonomous Driving Sensing Systems

Lead General Motors’ autonomous-driving sensing evaluation and validation systems. Guide simulation, sensor data, software architecture, and engineering teams.

USUnited StatesCACalifornia
$189,300 – $290,700 / year
HybridFull-timeSeniorEnglish RequiredFull-stack EngineerSoftware Engineer
BigQueryC++CloudLinuxPythonPyTorchSQLTensorflow

Description

  • Set the technical strategy for sensing-system evaluation frameworks
  • Integrate camera, LiDAR, RADAR, and other sensor models into simulation and evaluation environments
  • Develop statistical and empirical approaches to analyze sensor and perception performance
  • Create and oversee synthetic data from road-data replay, simulation, and scenario-generation pipelines
  • Define data augmentation and scenario coverage for nighttime, rain, snow, fog, contamination, cleaning, occlusion, glare, and other degraded conditions
  • Prepare synthetic and recorded data for model training, evaluation, regression testing, and failure analysis
  • Lead model retraining or pipeline demonstrations as needed
  • Incorporate new sensor components and sensing architectures into the autonomous-driving software stack
  • Specify developer tools such as APIs, command-line utilities, notebooks, automated workflows, and dashboards
  • Create evaluation metrics and reports that connect sensor performance with system requirements and safety objectives
  • Lead technical reviews and cross-functional initiatives from requirements definition through adoption
  • Advance software architecture, test coverage, data quality, automation, and engineering productivity
  • Mentor engineers and strengthen expectations for software quality and experimental rigor
  • Hire, coach, develop, and retain a strong engineering team while continuing to provide hands-on technical leadership

Requirements

  • Bachelor’s degree in computer science, computer engineering, electrical engineering, systems engineering, robotics, mathematics, or a related technical discipline
  • At least 10 years of progressive experience in software engineering, systems engineering, machine learning, perception, robotics, autonomous vehicles, or a related field
  • At least one year of experience leading a small engineering team
  • Experience directing complex technical initiatives across multiple engineering disciplines
  • Background designing, building, or integrating simulation, evaluation, validation, or data-processing systems in autonomy, robotics, automotive, aerospace, or another safety-critical field
  • Strong C++ and Python programming skills
  • Experience with machine-learning workflows and at least one modern framework, including PyTorch or TensorFlow
  • Knowledge of camera, LiDAR, RADAR, or multimodal sensing systems
  • Experience applying data, statistics, and structured experimentation to evaluate system behavior and diagnose failure modes
  • Ability to explain complex technical concepts clearly
  • Ability to work independently through ambiguous problems and deliver measurable outcomes
  • Experience with iterative development, code review, testing, version control, and agile planning
  • Demonstrated experience leading, coaching, or managing engineers
  • Preferred: Master’s degree or Ph.D. in computer science, engineering, robotics, mathematics, or a related technical field
  • Preferred experience with autonomous-vehicle perception and machine-learning models, adverse-condition sensor degradation, sensing architectures, synthetic data, scenario-based testing, sensor calibration, computer vision, multimodal fusion, safety-critical verification and validation, ROS, Linux, containers, continuous integration, distributed computing, cloud data platforms, metrics, dashboards, SQL/BigQuery, data visualization, statistical analysis, scalable sensor-data processing, and supplier or research partnerships

Benefits

  • Incentive compensation with payouts determined by company performance, job level, and individual performance
  • Company vehicle evaluation program, subject to a successful motor vehicle report review
  • Potential relocation assistance
  • Access to General Motors benefits and Total Rewards resources
  • Reasonable workplace accommodations

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