AI Research Intern (Unpaid)

Key Responsibilities

• Research & Development: Design, implement, and optimize machine learning models for high-accuracy face and hand detection and recognition systems.
• Image Processing: Apply state-of-the-art image processing techniques for feature extraction, data augmentation, and image pre-processing to enhance model performance.
• Model Training & Optimization: Conduct research on model architectures and training methodologies; implement quantization techniques to ensure models run efficiently on diverse devices and platforms.
• Data Management: Curate and preprocess large-scale datasets of images for training, validation, and testing; utilize data augmentation techniques to improve model robustness.
• Algorithm Improvement: Stay current with latest research papers and implement novel methods to improve model accuracy and efficiency, especially in face and hand detection.
• Performance Evaluation: Develop metrics for evaluating model performance, efficiency, and reliability; analyze results to fine-tune models and optimize for real-world applications.
• Collaboration: Work with cross-functional teams, including data engineers, software developers, and product managers, to understand project requirements and ensure seamless integration into end-user applications.

Technical Skills

• Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience with image processing libraries (e.g., OpenCV, PIL) and data manipulation tools.
• Expertise in designing and training convolutional neural networks (CNNs), specifically for object detection and recognition tasks.
• Hands-on experience with model quantization and compression techniques for efficient deployment on edge devices.
• Knowledge of key techniques in feature extraction, data augmentation, and image enhancement.
• Familiarity with relevant ML techniques (e.g., transfer learning, fine-tuning, ensemble methods).