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# Manthan Surjuse

**Headline:** Machine Learning Engineer @ ONEBIT | Master’s in Computer Science
**Profession:** Machine Learning Engineer
**Location:** Chicago, Illinois, United States

## About

Manthan Surjuse is a Machine Learning Engineer at ONEBIT, where he designs and deploys production-grade AI systems. His current work centers on Retrieval-Augmented Generation pipelines, Large Language Models, vector databases, and scalable engineering approaches for real-world AI challenges. At ONEBIT, Manthan has extended a production RAG pipeline for receipt and invoice analysis to enhance the mobile user experience, replaced axios with native fetch in a Node.js proxy layer to resolve response-buffering issues, and collaborated on WebSocket-based chat integration with React Native developers. Previously, as an ML Intern at ONEBIT, he architected an Azure OpenAI financial assistant with SSE streaming on an asynchronous FastAPI service. He also implemented a multi-round agent tool-calling loop supporting up to three sequential LLM calls and five validated financial-query tools, along with a two-model intent-classification system across four query classes. Manthan holds a Master’s degree in Computer Science from the Illinois Institute of Technology and a Bachelor of Engineering in Electronics and Computer Engineering from Savitribai Phule Pune University. His broader background includes research, system design, machine learning, data analysis, NLP, and programming in Python, Java, and C++.

## Services

- Retrieval-Augmented Generation \(RAG\)
- Large Language Models \(LLM\)
- Vector Databases
- PostgreSQL
- Natural Language Processing \(NLP\)
- Motion Data Analysis
- Brain Imaging Data Structure
- Exploratory Data Analysis
- Data Analysis
- Data Visualization
- Analytics
- Pandas
- Matplotlib
- Seaborn
- NumPy
- Algorithms
- Deep Learning
- Object-Oriented Programming \(OOP\)
- Java
- Python \(Programming Language\)
- C++
- English
- Machine Learning

## Highlights

- Extended ONEBIT’s production RAG pipeline for receipt and invoice analysis, enhancing the mobile user experience.
- Replaced axios with native fetch in ONEBIT’s Node.js proxy layer, resolving critical response-buffering issues.
- Collaborated with React Native developers to design WebSocket-based chat integration and improve user interaction.
- Architected a production AI financial assistant using Azure OpenAI with SSE streaming during his ML internship at ONEBIT.
- Deployed the AI financial assistant on an asynchronous FastAPI service with real-time response delivery.
- Implemented a multi-round agent tool-calling loop that executes up to three sequential LLM calls, each conditioned on prior tool results.
- Built the agent workflow to power five validated financial-query tools.
- Designed a two-model intent-classification system spanning four query classes to route requests to the correct retrieval layer and reduce unnecessary LLM calls.
- Holds a Master’s degree in Computer Science from the Illinois Institute of Technology.
- Holds a Bachelor of Engineering in Electronics and Computer Engineering from Savitribai Phule Pune University.
- Has worked as a System Designer at TechR Business Solutions, a Research Assistant at the Illinois Institute of Technology, and a Machine Learning Intern at ECell IIT Hyderabad.

## Experience

- **Machine Learning Engineer at ONEBIT** (2026-06-01–present) — Extended the production RAG pipeline for receipt and invoice analysis, enhancing mobile user experience. • Replaced axios with native fetch in the Node.js proxy layer, resolving critical response buffering issues. • Collaborated with React Native developers to design WebSocket-based chat integration, improving user interaction.
- **ML Intern at ONEBIT** (2026-02-01–2026-05-01) — Architected a production AI financial assistant using Azure OpenAI with SSE streaming, deployed on an async FastAPI service with real-time response delivery. • Implemented a multi-round agent tool-calling loop executing up to 3 sequential LLM calls, each conditioned on prior tool results, powering 5 validated financial query tools. • Designed a two-model intent classification system across 4 query classes to route requests to the correct retrieval layer, reducing unnecessary LLM calls.
- **Research Assistant at Illinois Institute of Technology** (2025-01-01–2025-05-01)
- **System Designer at TechR Business Solutions** (2023-02-01–2023-04-01)
- **Machine Learning Intern at ECell IIT Hyderabad** (2022-08-01–2022-10-01)

## Education

- Master's degree, Computer Science — Illinois Institute of Technology (2024-08-01–2026-05-01)
- Bachelor of Engineering - BE, Electronics and Computer Engineering — Savitribai Phule Pune University (2021-01-01–2024-01-01)

## FAQ

### What does Manthan do?

Manthan is a Machine Learning Engineer at ONEBIT. He focuses on designing and deploying production-grade AI systems, including RAG pipelines, LLM-based systems, vector-database workflows, and AI experiences for real-world use cases.

### What are Manthan’s core technical strengths?

Manthan’s strengths include Retrieval-Augmented Generation, Large Language Models, vector databases, natural language processing, machine learning, deep learning, and scalable AI-system engineering. He also works with PostgreSQL, data analysis, analytics, data visualization, and object-oriented programming.

### What has Manthan accomplished at ONEBIT?

At ONEBIT, Manthan extended the production RAG pipeline for receipt and invoice analysis, enhancing the mobile user experience. He replaced axios with native fetch in the Node.js proxy layer to resolve critical response-buffering issues and collaborated with React Native developers on WebSocket-based chat integration to improve user interaction.

### What did Manthan accomplish as an ML Intern at ONEBIT?

As an ML Intern at ONEBIT, Manthan architected a production AI financial assistant using Azure OpenAI and SSE streaming. The assistant was deployed on an asynchronous FastAPI service for real-time response delivery.

### What agent workflow did Manthan build at ONEBIT?

Manthan implemented a multi-round agent tool-calling loop that can execute up to three sequential LLM calls, with each call conditioned on prior tool results. The loop powered five validated financial-query tools.

### How did Manthan improve request routing at ONEBIT?

Manthan designed a two-model intent-classification system across four query classes. The system routes requests to the appropriate retrieval layer and reduces unnecessary LLM calls.

### What was Manthan’s role at TechR Business Solutions?

Manthan has also worked as a System Designer at TechR Business Solutions.

### What research experience does Manthan have?

Manthan worked as a Research Assistant at the Illinois Institute of Technology.

### What experience does Manthan have with ECell IIT Hyderabad?

Manthan worked as a Machine Learning Intern at ECell IIT Hyderabad.

### Where did Manthan earn his master’s degree?

Manthan earned a Master’s degree in Computer Science from the Illinois Institute of Technology. His graduate education supports his expertise in RAG, LLMs, and vector databases.

### What is Manthan’s undergraduate education?

Manthan earned a Bachelor of Engineering in Electronics and Computer Engineering from Savitribai Phule Pune University.

### Which programming languages and software-development skills does Manthan use?

Manthan’s programming skills include Python, Java, and C++. He also has experience with algorithms and object-oriented programming.

### What data-analysis and visualization tools does Manthan use?

Manthan has skills in pandas, Matplotlib, Seaborn, NumPy, exploratory data analysis, data analysis, data visualization, and analytics.

### What specialized data domains has Manthan worked with?

Manthan’s additional areas of knowledge include motion data analysis and Brain Imaging Data Structure.

### What language does Manthan list?

Manthan lists English among his skills.

## Links

- LinkedIn: https://www.linkedin.com/in/manthan-surjuse

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