Expertise

Skills & Expertise

25+ tools and technologies across ML, AI/RAG, backend engineering, and DevOps.

Proficiency Overview

Self-assessed proficiency levels based on project experience

Programming Languages

Python90%

SQL80%

JavaScript65%

Java60%

PHP50%

Machine Learning

Classification92%

Feature Engineering90%

SHAP Explainability88%

Anomaly Detection85%

Time Series85%

Clustering82%

AI & RAG Systems

RAG Pipelines90%

Vector Databases88%

LLM Integration85%

Text Embeddings85%

Cross-Encoder Reranking82%

Frameworks & Libraries

Scikit-learn92%

Pandas / NumPy90%

XGBoost / LightGBM88%

FastAPI85%

sentence-transformers85%

Flask80%

Databases & Vector Stores

FAISS88%

Qdrant85%

PostgreSQL (pgvector)80%

SQLite / MySQL78%

Redis75%

Deployment & DevOps

REST API Design88%

Git / GitHub85%

JWT Authentication82%

Docker80%

Rate Limiting / CORS / SSRF80%

Tools & Environment

Python

PostgreSQL

Docker

Git

GitHub

VS Code

Jupyter

Groq API

FastAPI

Flask

Redis

FAISS

Qdrant

Scikit-learn

LightGBM

XGBoost

Pandas

NumPy

SHAP

Prophet

JWT

SSRF / CORS

Linux / Bash

Kaggle

Currently Exploring

What's on my learning roadmap right now

GraphRAG

Knowledge graph-enhanced retrieval for complex multi-hop reasoning.

LLM Fine-tuning

LoRA/QLoRA fine-tuning strategies for domain-specific LLM adaptation.

Agentic AI

Multi-agent orchestration and tool-calling patterns for autonomous AI workflows.

Kubernetes

Container orchestration for scaling production ML inference services.