Rajesh Paruchuri - Portfolio

Email
rajeshchowdary930@gmail.com
Phone
+1 (408) 590-8932
Birthday
June 10, 2004
Location

San José, California, USA

About me

Hi, I'm Rajesh, a Research Assistant at San Jose State University, currently diving deep into the world of Agentic AI. My work involves building intelligent services and developing MCP servers to integrate them into larger systems.

What drives me? The ever-evolving landscape of AI/ML. There's something about this field that keeps me curious and constantly exploring new ideas. I'm not just interested in building things that work behind the scenes, I want to bring them to life on the frontend and see my creations live on the web.

Beyond code, I enjoy traveling, spending quiet time with myself, and making memories with the people I love. Being far from family isn't easy, but every step forward reminds me why I started this journey.

What i'm doing

Machine Learning & AI

Building and deploying ML models using TensorFlow, PyTorch, and scikit-learn for real-world applications.
Data Engineering & ETL

Architecting scalable data pipelines with Apache Airflow, SQL, and cloud platforms for data warehousing.
Backend Development & APIs

Developing REST APIs and microservices using Flask, FastAPI, and Java for production systems.
Cloud & DevOps

Deploying applications using Docker, Kubernetes, and AWS for scalable cloud-native solutions.

Resume

Education

M.S., Applied Data Intelligence
2025 — 2027
San José State University. Specializing in machine learning, data science, and AI research with focus on reinforcement learning and LLM integration.
B.Tech in Information Technology
2019 — 2023
Completed degree with focus on software development, data structures, databases, and fundamental AI/ML concepts.
Professional Certifications
2023 — Present
Pursuing certifications in advanced machine learning, cloud computing, and data engineering best practices.

Experience

AI Research Assistant
Sep 2025 — Present
Applied Data Science Research Lab, San José State University. Building RL and RAG systems integrating LLMs with RL algorithms, improving decision-making accuracy by 25% and achieving 20% faster convergence in agent training.
Machine Learning Engineer Intern
Aug 2023 — Dec 2023
SmartInternz (Remote). Engineered end-to-end ML pipeline for Bitcoin price prediction with 96-97% accuracy, optimized ETL pipeline reducing latency by 60%, and implemented automated retraining workflow maintaining 95%+ accuracy.
Software Developer
2022 — 2023
Developed full-stack applications with Python, JavaScript, and SQL. Collaborated on multiple projects involving data processing, API development, and database optimization.