Ejaz Habib Dar

Updated, tested, and integrated cutting-edge technologies into 'Federation AI' ChatBot application, enhancing user experience by enabling queries across 500+ documents.

• Conducted daily client meetings to gather requirements and implement feature enhancements, improving app efficiency and user satisfaction.
  Utilized advanced language models such as GPT-4, LLAMA-2, and Mistral 7B to enhance document processing capabilities, reducing query response time by 30%.
• Integrated project management tools like Jira, Assembla, and Okta into Chatbot for seamless team collaboration, increasing operational efficiency by 20%.

Specialized in computer vision tasks, including object detection, image classification, segmentation, and key point detection, utilizing tools like Open CV, YOLO, CNNs, TensorFlow, PyTorch, and Fast AI.

• Developed and deployed solutions that improved object detection accuracy by 15%, enhancing the efficiency of client applications.
• Trained and fine-tuned models on large datasets, reducing processing time by 20% while maintaining high accuracy.
• Collaborated with cross-functional teams to implement advanced image recognition pipelines, delivering results within tight deadlines.

• Solved complex machine learning challenges, including tasks such as image classification, causal and masked language modeling, speech-to-text, and text-to-speech processing.
• Trained and fine-tuned state-of-the-art models like GPT and BERT, enhancing model accuracy and reducing error rates by 15%.
• Leveraged advanced frameworks such as LangChain and Generative AI techniques using Stable Diffusion with LORA to develop innovative AI solutions.
• Delivered optimized AI pipelines that improved system performance, contributing to more efficient deployment of machine learning models across diverse use cases.