Consulting Cloud Architect, OpenShift
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Design and deliver Red Hat OpenShift, Kubernetes, and hybrid cloud solutions for enterprise customers. Lead customer engagements focused on infrastructure, automation, and application delivery.
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General Motors एक वैश्विक ऑटोमोटिव और विनिर्माण कंपनी है, जो वाहन इंजीनियरिंग, उत्पादन, परिवहन और सूचना प्रौद्योगिकी के क्षेत्रों में काम करती है। 1908 में स्थापित GM ऐसी तकनीकें विकसित करती है जिनका उद्देश्य गतिशीलता को आगे बढ़ाना है और साथ ही शून्य दुर्घटनाओं, शून्य उत्सर्जन तथा शून्य यातायात जाम के अपने दृष्टिकोण को साकार करना है। इसके अंतरराष्ट्रीय संचालन में नवाचार, टिकाऊ परिवहन और ऑटोमोटिव उद्योग के भविष्य पर केंद्रित बड़े, बहु-विषयक दल एक साथ काम करते हैं।
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.
संयुक्त राज्य
कैलिफ़ोर्निया$1,89,300 – $2,90,700 / वर्ष
हाइब्रिडपूर्णकालिकवरिष्ठआवश्यक भाषा: अंग्रेज़ीफुल-स्टैक इंजीनियरसॉफ्टवेयर इंजीनियरविवरण
- 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
आवश्यकताएँ
- 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
लाभ
- 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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