Tasks:
- * Build detection, classification, segmentation, tracking, and keypoint models
- * Deploy and accelerate inference on embedded and chip platforms
- * Develop lightweight on-device vision algorithms
- * Manage data collection, cleaning, annotation, and analysis
- * Optimize models through pruning, distillation, and quantization
- * Research and validate lightweight vision algorithms
- * Train, tune, and evaluate models
Perks/Benefits:
Skills/Tech stack required:
[C++] [Computer Vision] [Data Annotation] [Deep learning] [Edge Computing] [Embedded deployment] [Image classification] [Image Segmentation] [Inference acceleration] [Keypoint detection] [Knowledge Distillation] [Linux] [Model Evaluation] [Model Pruning] [Model Quantization] [Model Training] [Model Tuning] [Object Detection] [Object Tracking] [OpenCV] [Python] [PyTorch] [TensorFlow]
Educational requirements:
[Master's Degree]
Role(s):
[AI Engineer] [Computer Vision Engineer] [Edge AI Engineer] [Engineer] [Learning Engineer] [Machine Learning Engineer] [Vision Engineer]