AI Engineer

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 related quantitative field.
• Technical Proficiency\:
  • Expertise in common ML/DL frameworks (PyTorch, TensorFlow).
  • Strong programming skills in Python and C++ (essential for production-level embedded systems).
  • Hands-on experience with Computer Vision algorithms (e.g., object detection, semantic segmentation, tracking) and libraries like OpenCV.
  • Proven experience with automotive sensor data processing and Sensor Fusion techniques.
• Automotive Domain Knowledge\:
  • Familiarity with automotive communication protocols (CAN, Ethernet) and architectures.
  • Understanding of safety-critical systems and standards (ISO 26262).

✨ Preferred Skills (Nice to Have)

• Experience with MLOps practices and tools for model lifecycle management.
• Familiarity with automotive operating systems like AUTOSAR or QNX.
• Knowledge of simulation tools (e.g., CARLA, IPG CarMaker) for testing AI models.

Experience in reinforcement learning or predictive modeling for vehicle diagnostics or user behavior.