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.
