AI Engineer

 Responsibilities:

Design and Development

• Lead the end-to-end design, development, and implementation of AI/ML models, including Deep Learning models for perception, prediction, and control, for production automotive platforms.

Data Pipeline Management

• Develop and manage large-scale data pipelines for collection, cleaning, annotation, and augmentation of complex automotive sensor data (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 ECUs using techniques like quantization, pruning, and hardware acceleration.

Validation and Testing

• Collaborate with verification and validation teams to rigorously test AI models against safety-critical standards and real-world driving scenarios.

System Integration

• Integrate AI software components with vehicle operating systems and hardware/software subsystems to ensure seamless functionality and reliability.

Research and Innovation

• Stay updated with AI/ML research and automotive technologies, and proactively propose and prototype innovative solutions to enhance product performance.