AI Research Intern
Tasks
- Analyze failure cases under distribution shift
- Apply model compression techniques
- Conduct experimental design and ablation studies
- Curate and balance datasets
- Design deep learning models for computer vision
- Design efficient edge and embedded architectures
- Evaluate models with standard metrics
- Implement network and dataset pruning
- Perform quantization aware training and post training quantization
- Research CNNs and Vision Transformers
Perks/Benefits
- Conference submission support
- Edge deployment exposure
- Hands-on research experience
- Mentorship
- Opportunity to contribute to publications
- Research mentorship
Skills/Tech-stack
Ablation Studies | Bias Mitigation | Calibration | Computer Vision | Convolutional Neural Networks | Dataset Pruning | Dataset curation | Deep learning | Experiment tracking | IoU | Knowledge Distillation | MAP | MLflow | Model Compression | Network Pruning | Neural Networks | ONNX | Optimization | Post-training | Post-training Quantization | Probability | PyTorch | Quantization aware training | Reproducibility | TFLite | TensorRT | Vision Transformers | Weights and Biases
Education
N/A
Roles
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