Junior AI Engineer with a background in Electronics & Computer
Science and an Honors in AI & ML. I build practical solutions
using Machine Learning, Deep Learning, and Data Science.
I enjoy turning ideas into real projects — whether it's computer
vision systems, predictive ML models, LLM-based tools, or
analytics-driven insights. Currently focused on LLMs, RAG, AI
agents, MLOps, and real-world model deployment.
Always learning. Always building. 🚀
Work Experience
Junior AI Engineer
Softgainz Technologies • Full-time • Mumbai, India
· On-site
Develop and deploy AI/ML solutions using Python,
TensorFlow, and PyTorch to solve real-world problems and
improve system performance.
Process and analyze structured and unstructured data from
multiple sources; build ML and deep learning models for
predictive analytics and actionable insights.
Design interactive dashboards for data visualization and
business intelligence.
Collaborate with teams to integrate modern AI tools and
apply advanced algorithms and optimization techniques to
deliver scalable, efficient solutions.
Elite Projects Analyst — Instat IHFull-time • Aug 2025 – Feb 2026 • 7 mos
Worked with match recordings sent by coaches, using
Hudl's advanced tagging system to log specific events
and key moments throughout the game.
Broke down each play into granular components — player
movements, formations, and key actions — ensuring
precise data capture.
Processed data to generate comprehensive performance
metrics, providing coaches with actionable insights
for tactical adjustments and performance enhancement.
Elite Project Trainee — Instat IHInternship • Jul 2025 – Aug 2025 • 2
mos
A curated collection of
50 hands-on ML projects
designed to build a deep understanding of Large Language
Models from the ground up. Covers tokenization, attention
mechanisms, transformer architecture, fine-tuning, RAG
pipelines, and AI agents — with clean, well-documented
Jupyter notebooks.
A comprehensive Python project for analyzing real estate
and customer data, uncovering
market trends, building segmentation
models, and visualizing sales patterns. Includes EDA,
feature engineering, and interactive visual reports using
Matplotlib and Seaborn.
End-to-end customer segmentation pipeline using
K-Means & Hierarchical Clustering.
Includes data preprocessing, EDA, feature engineering,
cluster interpretation, and actionable marketing strategy
recommendations based on segment behavior.
LinkedIn
GitHub