Open to opportunities

Shreyash Mutha

@shreyashmutha

Message

AI & Quantitative Research enthusiast building fast, production-ready ML systems and pricing models.

India

Message

What I'm looking for

I’m looking for an early-career role where I can combine quantitative thinking and ML engineering—building validated models and low-latency, production-ready systems, collaborating closely with research and product to ship measurable impact.

I’m a B.Tech student in Computer Science with AI & Data Science, focused on turning machine learning into reliable, decision-grade products. My work spans quantitative modeling, predictive ML pipelines, and AI systems designed for real-world constraints like latency, uptime, and validation.

At JPMorgan Chase & Co., I built a probability-of-default model and an expected-loss pipeline, and I designed a natural gas storage contract pricing engine to compute fair value. In industry, I streamlined ML pipeline workflows (cutting training time by 30%), built an AI-powered calling platform using Twilio and OpenAI/Whisper with sub-200ms response targets, and delivered interactive model visualization that reduced review time by 40%. I also prototype with computer vision and market intelligence dashboards—e.g., YOLOv8-based parking violation detection across 10+ camera feeds—and I publish research and technical writing while staying strongly process-driven through CI/CD and tested deployments.

Experience

Work history, roles, and key accomplishments

Software Development Intern

Reurja Technologies

Jan 2026 - Apr 2026 (3 months)

Engineered an AI-powered calling platform using Twilio for voice and OpenAI/Whisper for speech-to-text and NLP, orchestrated with LangChain and exposed via Node.js/Express.js REST APIs. Implemented CI/CD and deployed to Firebase, supporting production reliability and an NLP-driven call routing system.

Twilio OpenAI Whisper Speech to Text NLP Lang Chain Node REST APIs MongoDB CI CD Firebase

AI Intern

Automaton AI Infosystem Pvt. Ltd.

Dec 2024 - Jan 2025 (1 month)

Streamlined predictive ML pipelines across ingestion, preprocessing, model selection, and hyperparameter tuning to reduce training time by 30% and increase throughput. Built an automated model-selection module and launched an interactive frontend to visualize real-time model outputs.

predictive modeling data preprocessing Selection Models Hyperparameter Tuning Automated Algorithm Selection Real Time Model Output Visualization

Quantitative Research Forage Simulation

JPMorgan Chase & Co.

Jan 2026 - Present (7 months)

Developed a probability-of-default model using FICO quantile-binning with Logistic Regression and validated with ROC-AUC, along with an Expected Loss pipeline combining PD and LGD assumptions. Designed a natural gas storage contract pricing engine to simulate injection/withdrawal cash flows and compute fair value under capacity constraints and holding costs.

FICO Quantile Binning Logistic Regression Decision Trees ROC AUC Probability Of Default (PD)LGD Risk Modeling

Education

Degrees, certifications, and relevant coursework

Vishwakarma Institute of Technology

Bachelor of Technology (B.Tech), Computer Science (AI & Data Science)

2023 - 2027

Pursuing a B.Tech in Computer Science with a focus on AI & Data Science, with coursework in algorithms, machine learning, deep learning, and database systems.