Final-year M.Tech (CSE – AI & ML) student with strong hands-on experience in Large Language Models (LLMs), NLP, and Deep Learning. Skilled in fine-tuning transformer models (LoRA/QLoRA), building AI pipelines, and optimizing inference for real-world applications. Currently working as a Data Science Intern at PowerSchool India.
I specialize in applied AI with a strong mathematical understanding of machine learning and deep learning models. My interests lie in LLM fine-tuning, NLP pipelines, generative AI applications, and scalable AI systems. I enjoy building end-to-end solutions that move beyond research into production.
Expertise & Tools
Python (Advanced), SQL, C/C++, Java (Basics)
Machine Learning, Deep Learning, Neural Networks, Model Mathematics
Transformers, BERT, Instruction Tuning, LoRA / QLoRA
Prompt Engineering, RAG (Foundations), LLM Applications
PyTorch, TensorFlow, Scikit-learn, Hugging Face
Pandas, NumPy, ETL Pipelines, Feature Engineering
REST APIs, Flask, FastAPI (Basics)
Linux Basics, Docker (Basics), Git, GitHub
VIT Vellore | CGPA: 9.07 | 2024 – 2026
JNTU Hyderabad | CGPA: 7.97 | 2020 – 2024
Jul 2024 – Present
Built data pipelines, performed EDA and statistical analysis, supported ML model training, fine-tuning, and optimization using Python, Pandas, NumPy, and SQL.
Fine-tuned transformer-based LLMs using instruction tuning and PEFT (LoRA/QLoRA). Built NLP pipelines for NER, text classification, and semantic search, achieving ~85% accuracy. Developed low-latency LLM applications using Gradio.
Implemented a deep learning-based face recognition system using OpenCV with cloud-based inference. Deployed using AWS Lambda focusing on real-time performance, scalability, and reliability.
Let's connect and create something amazing