Pranam Shetty
Rochester, NY
AI Developer. ML Engineer. I finetune models, build scalable pipelines and automate workflows.
What I work with
Experience
AI Engineer Intern
May 2025 - Aug 2025
United States
Conducting research on LLM performance and applicability to investment and wealth advisory work.
ML Engineer Intern
June 2023 - Aug 2023
India
Developed deep learning models for financial stock prediction and real-time data visualization.
ML Research Intern
Sept 2021 - Nov 2021
India
Built and optimized ML pipelines for insurance claim cost prediction and big data processing.
SEO Analytics Intern
Feb 2020 - March 2020
India
Managed digital advertising strategies to optimize conversions for educational courses.
Open Source Contributor
Jun 2024 - Now
Contributed to langchain, huggingface, raycast, and other open source projects
Projects
CodeClimax
A Chrome extension that celebrates your problem-solving successes with custom media. When you solve a LeetCode problem, the extension detects your success and displays a celebration overlay with your chosen media.
Hugo Noir
A clean, minimalistic theme for Hugo with a focus on readability, simplicity, and multilingual support.
Blogs
2025-09-07
Attention Is Not All You Need. It's How You Need It.
Jet-Nemotron rethinks AI by using attention only when necessary, dramatically boosting speed and accuracy compared to traditional full-attention models.
2025-08-23
Are LLMs Needlessly Huge? Extreme Compression of LLMs using Quantum Inspired Tensor Networks
Presents a novel approach called CompactifAI by Multiverse Computing, which uses quantum-inspired tensor networks to drastically compress LLMs with minimal loss in accuracy.
2025-08-16
How AI Models Train on Private Data Without Accessing It: Federated Learning Explained
Federated Learning (FL) enables AI models to be trained on distributed data without centralizing sensitive information. Instead of collecting data in one location, FL sends model copies to local devices where they train on private data.