Professional Overview
B.E.+4 yrs + Python+Data Science + SQL+ Unix+ Pandas + Numpy + Scikit-learn + Matplotlib + Django + NLP +TensorFlow Flask+SQL Alchemy+REST API+AGILE+Git + Pytest + AWS+Devops+machine learning+artificial+ intelligence+etl+data warehouse+business intelligence+mongo db+ LLM+agentic ai+etl+data warehouse+business intelligence
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
