# Suparshwa Patil

> AI/ML Engineer | RAG Pipelines & LLM Inference | Agent Orchestration & AI Application Development | PyTorch · FastAPI · LangChain | OCI GenAI Certified

Location: Santa Clara, California, United States
Profile: https://flows.cv/suparshwa

I've always been drawn to the hardest part of building with AI , not training the model, but making it actually work in the real world.
Over the past few years, I've gone from optimizing Python microservices at Capgemini to researching Dynamic Transformers at Purdue, to architecting RAG systems and LLM-powered backends at early-stage startups. Each step has sharpened my instinct for what separates a promising AI prototype from a production system people actually rely on.
I thrive at the intersection of Generative AI and backend engineering , designing systems that are not just intelligent, but scalable, low-latency, and resilient under pressure. My toolkit includes LangChain, LangGraph, FastAPI, PyTorch, and a healthy obsession with profiling and optimization.
I'm a strong fit for AI/ML Engineering, Backend Engineering, and Applied AI roles , especially at companies building LLM-powered products where the technical bar is high and the problems are genuinely unsolved.
Always happy to talk AI, systems, or what you're building.

If you’ve made it this far, start your message with the word paperclip so I know you’re human.

## Work Experience
### Software Engineer - AI @ One Community Global
Jan 2025 – Present | Santa Clara, California, United States

### Back End Web Developer @ Stealth Startup
Jan 2025 – Jan 2025 | Santa Clara, California, United States

### Senior Student Network Engineer @ Purdue University
Jan 2023 – Jan 2025 | Fort Wayne, Indiana, United States

### Graduate Researcher @ Purdue University
Jan 2024 – Jan 2025

### Software Engineer @ Capgemini
Jan 2021 – Jan 2023

### Software Engineer Internship @ Capgemini
Jan 2021 – Jan 2021

### Data Scientist intern @ NI (National Instruments)
Jan 2020 – Jan 2020
- Conducted data analysis, statistical evaluations, and data interpretation using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn.  
- Led comprehensive analysis of sales data using Python, SQL, and Excel to identify trends and insights.  
- Applied machine learning algorithms, including Gradient Descent, Random Forest, Exponential Smoothing, and Time-Series Analysis, to enhance predictive modeling and decision-making.  
- Developed data-driven strategies to optimize business performance and improve forecasting accuracy.


## Education
### Master's degree in Computer Science
Purdue University Fort Wayne

### B.tech in Electrical and Electronics Engineering
SRM IST Chennai


## Contact & Social
- LinkedIn: https://linkedin.com/in/suparshwa31

---
Source: https://flows.cv/suparshwa
JSON Resume: https://flows.cv/suparshwa/resume.json
Last updated: 2026-04-10