03Experience
A short résumé.
Four roles, four years, one obsession: shipping production ML systems that work outside the notebook.
Machine Learning Engineer - II
Skylark Labs- Developed a production-grade visual tracking system featuring a 7D Kalman filter for multi-object tracking and predictive PiP stabilization. Built an offline standalone tracker with Camera Motion Compensation using sparse optical flow and affine estimation, handling complex re-identification and dynamic state switches.
- Optimized inference by deploying a TensorRT-optimized model on NVIDIA Triton Inference Server, doubling throughput from 3 FPS to 6–7 FPS via profiling and optimized post-processing logic over gRPC.
- Architected and developed Drishti, a distributed annotation system processing video datasets with GPU-accelerated YOLO inference on Celery workers, automated quality control, smart work distribution, and real-time batch processing, deployed as a full-stack solution (Django + React + PostgreSQL + Docker) with Cloudflare R2 integration, improving annotation throughput by 3x.
- Worked on continuous training and validation of a YOLO-based object detection model, including hyperparameter tuning and false-positive analysis.
Data Scientist
Emergys- Designed and implemented, as an individual contributor, a comprehensive dashboard for detecting price outliers in product flavor data, incorporating clustering analysis, supplier concentration metrics, and portfolio optimization techniques.
- Built a promo-sales forecasting engine using Gradient Boosting (R2: 0.93) on Azure Databricks; automated optimization using TPE-based recommender to suggest an optimal promotional strategy.
- Led the development of SQL AI Agent for BI dashboards using fine-tuned LLMs, React/Tailwind frontend, and Django/Docker backend, delivering sub-5s queries and deployed across multiple enterprise clients, evolving into a core revenue-generating product and reducing query turnaround time by 90%.
SDE Intern
Atomic Loops- Engineered backend REST APIs using Django REST Framework for diverse products, facilitating data generation and collection for training ML models. Designed and implemented app for Yoga pose detection using Flutter.
- Implemented a Real-time Chat API using WebRTC for a client's website.
- Designed and implemented app for Yoga pose detection using Flutter.
ML Intern
Nishikawa Communications Pvt. Ltd.- Developed an image straightener tool using OpenCV and TesseractOCR. This system automatically corrects titled or flipped images, delivering results in a rapid response time of 1-2 seconds.
- Built Japanese character classifier, utilizing transfer learning to recognize Hiragana and Katakana characters. The model was containerized using Docker for easy deployment.
- Increased efficiency by writing custom Python scripts for data analysis after getting data from Google My Business API by using pandas. Updated the older script to match newer version of the API.