- Deep Learning Frameworks: PyTorch
- Programming: Python (Advanced), OOP (Object-Oriented Programming).
- Computer Vision Tasks: Object Detection, Semantic Segmentation, Instance Segmentation, Multi-Object Tracking (MOT), Lane Detection.
- Libraries: OpenCV, NumPy, Scikit-learn, TorchVision.
- Model Optimization: TensorRT, ONNX, Quantization (INT8/FP16), Pruning, Model Compression.
- Architectures: Transformers (ViT), ResNet, YOLO (v8/v10), Mask R-CNN, DeepSORT.
- Infrastructure: Docker, CUDA, Git, MLOps.
Automotive & BEV Specialized Terms
- BEV (Birds Eye View): Perspective Transformation, Spatial-Temporal Transformers, Lift-Splat-Shoot (LSS).
- Autonomous Driving (AD): ADAS (Advanced Driver Assistance Systems), Perception Pipeline, Sensor Fusion.
- Sensor Modalities: LiDAR, Radar, Camera-only (Vision-centric), Ultrasonic.
- Data Formats: Point Clouds, NuScenes Dataset, KITTI Dataset, Waymo Open Dataset.
📌 Artificial Intelligence Engineer (Chennai)
🏢 Valeo
📍 Chennai