AI Engineer - Canvas Solution
(2026-02 - 2026-04)
- Built ASA-Agent, a production multi-agent healthcare assistant using LangGraph and LangChain with intent routing across scheduling, emergency, cancellation, and FAQ workflows.
- Designed dual RAG pipeline strategy (FaqNode & FaqNodeNoTool) with optimized chunking strategies, embedding models, and context window management for medical knowledge retrieval.
- Implemented semantic search via pgvector (PostgreSQL) for dense embedding storage and retrieval; applied re-ranking logic to improve answer faithfulness.
- Enforced structured outputs using Pydantic schemas; monitored model performance using MLflow to track inference quality and latency tradeoffs.
- Applied NLP techniques including intent classification and entity extraction to route patient queries across specialized agents.
AI Data Annotator / ML Intern - Unpeel (Startup)
(2025-12 - 2026-02)
- Collected and structured children's fashion product datasets across 19 brands for training ML classification models.
- Labeled and validated product attributes (gender, clothing type, brand) to support NLP-based text classification pipelines.
- Supported the full ML pipeline: data collection to labeling to preprocessing to model training preparation.
Machine Learning / Deep Learning Fellow - Buildables
(2025-07 - 2025-11)
Completed 3-month intensive fellowship in ML and Deep Learning; worked on research-driven practical AI projects.
- Received strong mentor recommendation for exceptional performance.
Junior Data Scientist & AI Engineer - IT Directorate
(2024-06 - 2024-12)
- Analyzed organizational data using Python and scikit-learn to build models supporting 3+ strategic decisions by department leadership.
- Built predictive dashboards for sales and customer analytics, reducing manual reporting time by ~40% and improving insight turnaround.
- Led AI-driven automation projects using TensorFlow/Keras, eliminating repetitive manual processes across 2 operational workflows.
