MBRDI
Automotive
AIEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“AI Engineer at MBRDI. Skills: AI/ML models, Deep Learning, Computer Vision, Sensor Fusion. Lead design of AI/ML models. Develop AI/ML models”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
3–5 years of professional experience in AI/ML solutions, Experience in the automotive domain, Bachelor’s or Master’s degree, Expertise in PyTorch, Expertise in TensorFlow, Programming skills in Python, Programming skills in C++, Hands-on experience with Computer Vision algorithms, Experience with OpenCV, Proven experience with automotive sensor data processing, Proven experience with Sensor Fusion techniques, Familiarity with automotive communication protocols, Familiarity with CAN, Familiarity with Ethernet, Understanding of safety-critical systems, Understanding of ISO 26262
Nice to Have
Experience with MLOps practices, Experience with model lifecycle management, Familiarity with AUTOSAR, Familiarity with QNX, Knowledge of simulation tools, Experience in reinforcement learning, Experience in predictive modeling, Domain knowledge in automotive engineering, Exposure to international projects, Exposure to global stakeholder management, Experience with Daimler systems
What You'll Do.
Lead design of AI/ML models
Implement AI/ML models
Develop data pipelines
Manage data pipelines
Collect automotive sensor data
Clean automotive sensor data
Annotate automotive sensor data
Augment automotive sensor data
Integrate AI software components
Propose innovative solutions
Prototype innovative solutions
How You'll Work.
Team & Collaboration
Verification and validation teams; Cross-functional teams
Full Job Description
About MBRDI: Mercedes-Benz Research and Development India (MBRDI), headquartered in Bengaluru with a satellite office in Pune, is the largest R&D center for Mercedes-Benz Group AG outside of Germany. Our mission is to drive innovation and excellence in automotive engineering, digitalization, and sustainable mobility solutions, shaping the future of mobility. Key Responsibilities: Design and Development: Lead the end-to-end design, development, and implementation of robust AI/ML models (e.g., Deep Learning models for perception, prediction, and control) for production use in automotive platforms. Data Pipeline Management: Develop and manage large-scale data pipelines for the collection, cleaning, annotation, and augmentation of complex automotive sensor data (e.g., LiDAR, RADAR, camera, ultrasonic) required for model training and validation. Model Optimization and Deployment: Optimize ML models for performance, latency, and memory constraints on Edge devices and automotive-grade Electronic Control Units (ECUs) , utilizing techniques like quantization, pruning, and hardware acceleration. Validation and Testing: Collaborate with verification and validation (V&V) teams to rigorously test and evaluate AI models against safety-critical standards and real-world driving scenarios. System Integration: Integrate developed AI software components with the vehicle’s operating system and other hardware/software subsystems, ensuring seamless functionality and reliability. Research and Innovation: Stay abreast of the latest AI/ML research and automotive technologies, proactively proposing and prototyping innovative solutions to enhance product performance and features. Required Qualifications Experience: 3–5 years of professional experience in developing and deploying AI/ML solutions, with a significant portion of this experience directly in the automotive domain . Education: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a relat
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