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General Motors
General Motors
Sponsor pentru viza H1BIndustria autoIndustria prelucrătoareTransport
General Motors este o companie globală din industria auto și de producție, care activează în domeniile ingineriei vehiculelor, producției, transporturilor și tehnologiei informației. Fondată în 1908, GM dezvoltă tehnologii menite să avanseze mobilitatea, urmărindu-și în același timp viziunea de zero accidente, zero emisii și zero congestie. Operațiunile sale internaționale reunesc echipe numeroase și multidisciplinare, axate pe inovare, transport sustenabil și viitorul industriei auto.
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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.

USStatele Unite ale AmericiiCACalifornia
189.300 $ – 290.700 $ / an
HibridNormă întreagăSeniorLimbă Obligatorie: englezăInginer full-stackInginer software
BigQueryC++CloudLinuxPythonPyTorchSQLTensorFlow

Descriere

  • 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

Cerințe

  • 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

Beneficii

  • 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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