Overview In this role you will lead the architecture and development of sensing-system evaluation capabilities for GM's autonomous-driving efforts. You'll shape how camera, LiDAR, and RADAR systems are characterized, simulated, and validated across representative driving conditions, driving robust, scalable perception. You'll work across sensing, perception, ML, simulation, and vehicle integration to turn experiments into engineering decisions. This is a hands-on leadership role with broad technical influence and a focus on safety and reliability. Compensation / BenefitsRemote/hybrid work optionsBonus potentialCompany vehicle programRelocation benefits may applyCompetitive salary rangeTotal rewards resources ResponsibilitiesSet technical direction for sensing-system evaluation frameworks measuring performance, robustness, and readinessLead integration of camera, LiDAR, RADAR, and sensor models into simulation and evaluation environmentsDevelop statistical and empirical methods with experiment design, confidence measures, and trend analysisGenerate and manage synthetic data at scale from road-data replay, simulation, and scenario-generation pipelinesDesign data augmentation and scenario coverage for challenging conditions (nighttime, rain, snow, fog, occlusion, glare)Collaborate with ML and perception teams to prepare datasets for training, evaluation, and regression testingIntegrate new sensor components into the autonomous driving software stack and assess risks across releasesDefine and improve developer tools for sensing experiments (APIs, CLIs, notebooks, dashboards)Develop evaluation metrics and reporting linking sensor performance to system requirements and architecture trade-offsLead cross-domain reviews and align multiple teams to common objectivesIdentify opportunities to improve software architecture, data quality, automation, and productivityMentor engineers and raise software quality, rigor, and ownershipHire, coach, and retain a small high-performing team with hands-on leadership Key requirementsBachelor's degree in a technical fieldTen+ years in software/systems engineering, ML, perception, robotics, or related field1+ year of leadership experienceExperience leading multi-discipline technical initiativesExperience designing or integrating simulation/evaluation/data-processing systems for autonomy or safety-critical domainsStrong C++ and Python production-quality software skillsExperience with ML workflows and frameworks (PyTorch or TensorFlow)Understanding of sensing systems (camera/LiDAR/RADAR) and engineering trade-offsData-driven evaluation using statistics and experiments to identify failures and inform decisionsAbility to communicate complex concepts in reviews, docs, and cross-functional settingsIndependent, able to navigate ambiguity, set priorities, and deliver resultsExperience with iterative software development, code review, testing, VCS, and Agile planningDemonstrated leadership, coaching, and building inclusive, high-performing teamsCross-functional collaborationStrong communicationMentorship and team developmentC++PythonPyTorch
Not specified in the original listing.
Not specified in the original listing.
General Motors is a global automotive corporation known for its commitment to innovation, quality, and customer satisfaction. With a strong focus on sustainability and technological advancement, GM plays a pivotal role in the automotive industry. Read More