</ Arnav Bhilwariya />

AI/ML Engineer

building things that learn

[ view projects ][ download resume ][ github ↗ ]

// about

I'm an AI/ML enthusiast focused on building intelligent systems, data-driven applications, and scalable software. I enjoy turning ideas into products, experimenting with machine learning models, and exploring how AI can solve real-world problems.

ML / AI

[ Python ][ Scikit-learn ][ LightGBM ][ TensorFlow ][ Keras ][ NumPy ][ Pandas ][ Matplotlib ][ Seaborn ]

Concepts

[ Machine Learning ][ Feature Engineering ][ Time Series Forecasting ][ Model Deployment ][ Signal Processing ][ Data Pipeline Design ]

Backend

[ FastAPI ][ Flask ][ Django ][ Node.js ][ REST API Design ]

Languages

[ Python ][ C++ ][ JavaScript ][ Java ][ SQL ]

Tools

[ Git ][ GitHub ][ AWS EC2 ][ Google Colab ][ Linux ]

✦ Deloitte Australia — Technology Job Simulation, 2025

✦ AlgoUniversity — Graph Theory Camp, 2025

// experience

Turning Data Into Deployable ML Systems

During my internship at AD Infocom Systems, I worked across the ML lifecycle—from preparing data and engineering features to deploying prediction services through APIs.

I helped build:

Data pipelines that automated dataset creation and preprocessing.
FastAPI services for real-time model inference.
Production-ready workflows that connected machine learning models with business applications.
Scalable backend components supporting data science and engineering teams.

// projects

Goal-Directed Active Vision System

Built a goal-directed visual search agent using CLIP ViT-L/14 and Inverse Reinforcement Learning trained on COCO-Search18 dataset. Outperformed passive baseline on target localization accuracy. Pipeline: frame sampling → CLIP feature extraction → IRL-based policy learning → fixation prediction evaluation.

[ PyTorch ][ CLIP ViT-L/14 ][ OpenCV ][ IRL ][ Computer Vision ]

github ↗

Retail Demand Forecasting

Time-series demand forecasting system predicting daily sales across 50+ stores and 3,000+ items. Trained LightGBM achieving MAE 1.38 and RMSE 2.01, outperforming baseline by 22%.

[ LightGBM ][ Time Series ][ Python ][ Scikit-learn ][ Pandas ]

github ↗

Sparrow: AI Voice Coaching Platform

AI-driven voice analysis system extracting acoustic features (pitch, clarity, pacing) via signal processing. Delivers real-time structured coaching feedback with session-level improvement tracking.

[ Machine Learning ][ Signal Processing ][ librosa ][ Scikit-learn ][ Python ]

github ↗

// open source

merged