Sarang K.

Skills

Python, Java, R, TensorFlow, PyTorch, JAX, Hugging Face, LangChain, LangGraph, LangSmith, ONNX, TensorRT, cuDF, Pandas, NumPy, Scikit-learn, SQL, MongoDB, Pinecone, ChromaDB, SQLite, BigQuery, Hadoop, PySpark, ETL, AI Agents (Autogen, Phidata, CrewAI, Ollama), GCP, AWS, Azure, Vertex AI, Scalable Machine Learning, RAG, Model Fine-Tuning (LoRA, QLoRA), Quantization, Pruning, Distillation, Reinforcement Learning, Gradient Optimization, Distributed Systems, High-Performance Machine Learning, Data Preprocessing, Feature Engineering, Data Visualization (Tableau, PowerBI), Flask, Streamlit, Leadership, Mentorship

About

I am a passionate AI/ML Developer, Data Scientist and Software Engineer currently pursuing my graduate studies in Computer Engineering at New York University (NYU). My work spans academia and industry, focusing primarily on scalable AI solutions, data-driven decision-making, and software optimization.

Talking about my past experiences, I interned with Walmart Global Tech as a Data Science III Intern in the Store Assortment Optimization (Merchant Data Science) team in Summer 2025 building scalable Agentic RAG pipelines. I have led impactful AI/ML projects at the Indian Institute of Technology (IIT), Cloud Counselage Pvt Ltd, and Rejolut, specializing in fine-tuning open-source LLMs, optimizing inference pipelines, and mentoring over 200 interns. At Cloud Counselage, I developed an AI-powered evaluation system that reduced assessment time by 60% and significantly enhanced candidate evaluation processes. My work has also included impactful projects like the Adaptive MCQ Testing System, which benefited over 5,000 rural students, securing a national victory at the Smart India Hackathon 2023.

I have won several hackathons and competitions, including DataHack 1.0 and the 'Best Software Project' award at Trinity TechExpo 2024. Additionally, I've received the Industry Academia Excellence Award, was honored with an invitation to meet Goldman Sachs' Senior Engineering Team in New York, and have shared insights in podcasts and panel discussions. My research contributions are published in reputed journals, and I continuously explore innovations in AI agent systems, large language models (LLMs), and optimization frameworks.