About Me

Professional Summary

Highly accomplished ML Engineer with 4 years of progressive experience in Generative AI and Large Language Models (LLMs), spanning industry and research. Proven expertise in designing, building, and deploying AI systems using PyTorch, Hugging Face, LangChain, and VLLM. Adept in Natural Language Processing (NLP), model optimization, and scalable cloud deployment (AWS, Docker).

Seeking an ML Engineer, Generative AI Engineer, or AI Research Scientist role to develop and implement advanced, intelligent, and scalable AI solutions.

Key Highlights

Expertise & Experience

✓ Experienced in analyzing complex user needs and translating them into robust, functional AI-driven solutions
✓ Strong background in Object-Oriented Programming (OOP) principles and scalable software architecture
✓ Expertise in Python, PyTorch, Hugging Face, LangChain, and VLLM for Machine Learning
✓ Proficient in full-stack development (React.js, HTML, CSS, JavaScript, Python, SQL/NoSQL)

Methodology & Skills

✓ Hands-on experience with Agile methodologies (Scrum, Kanban)
✓ Skilled in debugging, optimizing, and resolving complex software and ML model issues
✓ Experience working effectively in collaborative, cross-functional, and global teams
✓ Strong analytical and problem-solving skills with excellent communication abilities

Education

Masters in Computer Science

University of North Texas

January 2023 - December 2024

GPA: 4.0/4.0

Specialized in Machine Learning, AI Research, and Responsible AI. Conducted research under Dr. Feng Yunhe focusing on ethical AI deployment and multi-agent systems.

Bachelors in Information Technology

Jawaharlal Nehru Technological University of Hyderabad, India

June 2018 - May 2022

GPA: 3.6/4.0

Focused on software engineering, database systems, and web technologies. Served as Teaching Assistant and Academic Advisor during final year.

Certifications

Ray Certified

Ray Framework Certification

Certified in Ray distributed computing framework for scalable machine learning and Python applications. Expertise in distributed training, hyperparameter tuning, and scalable ML workloads.

Machine Learning

Andrew Ng - Coursera

Comprehensive course covering supervised learning, unsupervised learning, neural networks, and deep learning fundamentals.

Algorithmic Toolbox

Coursera

Advanced algorithms and data structures, problem-solving techniques, and computational thinking.

Technical Skills

Tech Stack

🐍

Python

🔥

PyTorch

⚛️

React

▲

Next.js

⚡

VLLM

☁️

AWS

🐳

Docker

🍃

MongoDB

🚀

FastAPI

📝

TypeScript

🔗

LangChain

🤗

Hugging Face

🌿

Celery

🔴

Redis

☸️

Kubernetes

Programming Languages

🐍

Python

📘

C

📊

MATLAB

🌐

HTML/CSS

⚡

JavaScript

📝

TypeScript

🗄️

SQL

📄

LaTeX

Machine Learning & AI

🧠

Supervised Learning

🔍

Unsupervised Learning

🕸️

Deep Learning

💬

NLP

👁️

Computer Vision

🎯

Reinforcement Learning

✨

Generative AI

🔄

Transfer Learning

🤖

Multi-Agent Systems

📊

Model Evaluation

⚙️

Hyperparameter Tuning

🔬

Explainable AI (XAI)

Frameworks & Libraries

🔥

PyTorch

📚

TensorFlow

🤗

Hugging Face

🔗

LangChain

⚡

VLLM

🎨

Gradio

📊

Scikit-learn

🐼

Pandas

🔢

NumPy

⚛️

React.js

▲

Next.js

🌐

Django/Flask

⚡

Ray

Cloud & DevOps

AWS

🐳

Docker

☸️

Kubernetes

🔧

Jenkins

📈

Dynatrace

🔐

Git/GitHub

🔷

Azure DevOps

Databases

🗄️

PostgreSQL

💾

SQL Server

🔷

Oracle

🍃

MongoDB

Additional Skills & Attributes

Collaboration

Proven ability to work in global teams across multiple time zones, engaging with diverse stakeholders to achieve project goals.

Continuous Learning

Passion for staying updated with emerging technologies and latest developments in AI/ML research.

Leadership

Strong collaboration and leadership potential, with effective time management and organizational skills.