MD ALI ARMAGHAN

Developed, fine-tuned, and deployed LLMs for banking automation, improving AI response accuracy by 30%.

Built and optimized custom RAG pipelines using FAISS and ChromaDB, significantly enhancing retrieval efficiency.

Trained and fine-tuned transformer models (LLaMA, GPT) using LoRA and QLoRA, resulting in reduced model memory usage.

Integrated AI models with FastAPI and deployed on AWS SageMaker for seamless real-time interactions.

Conducted comprehensive LLM evaluations using perplexity scores, BLEU, ROUGE, and human feedback loops to drive continuous improvement.

Engineered and optimized AI-powered code generation models, increasing accuracy by 50%.

Fine-tuned models for specialized tasks including code completion, bug detection, and code refactoring.

Implemented Reinforcement Learning from Human Feedback (RLHF) for model evaluation, ensuring correctness and reducing bias in AI-generated code.

Automated model training and deployment workflows utilizing Hugging Face Spaces and AWS Lambda.

Developed and deployed a salary prediction model using Scikit-learn, improving accuracy by 15%.

Processed and analyzed over 100,000 employee records using Pandas and SQL, applying robust feature engineering techniques.

Built a resume screening system utilizing NLP techniques (TF-IDF, Word2Vec), significantly improving recruitment efficiency.

Collaborated with engineering teams to deploy AI models and meticulously documented findings for continuous improvement.