AI/ML Engineer - Codify Software Services - GCP
(2025-06)
Agentic AI Customer Support Automation System
- Built a multi-agent AI workflow using LangGraph and Gemini via Vertex AI to automate customer support tasks including refunds, order tracking, and query handling through intent-based routing.
- Designed a RAG pipeline using LangChain and Pinecone, improving retrieval relevance through chunking optimization, overlap tuning, and prompt engineering
- Developed intent classification and agent-routing workflows to manage retrieval, API execution, and fallback handling
- Reduced LLM inference cost by ~40% through model routing between Gemini Flash for lightweight queries and Gemini Pro for complex multi-step reasoning tasks
- Deployed scalable FastAPI services on Cloud Run with asynchronous request handling and automated CI/CD pipelines using Cloud Build
AI/ML Engineer - PHN Technology - AWS
(2024-06 - 2025-06)
Multilingual RAG GenAI EdTech Assistant
- Built a multilingual RAG assistant supporting educational queries across Hindi, English, Marathi, and Telugu using LangChain, Sentence Transformers, and Pinecone
- Implemented hybrid retrieval using BM25, semantic search, and RRF fusion with reranking, improving RAGAS answer relevance from 0.61 to 0.82
- Reduced end-to-end response latency by ~50% using Redis semantic caching and async retrieval pipelines
- Engineered modular AI pipelines with retrieval, reranking, guardrails, and fallback orchestration; tracked experiments and retrieval optimization workflows using MLflow
- Containerized and deployed AI services using Docker and AWS EC2 for scalable inference and reproducible experimentation
AI/ML Engineer - PHN Technology
(2024-06 - 2025-06)
ASTER Humanoid Robot AI-Based Embedded System
- Built a real-time pose-mimicking system using MediaPipe Holistic and Raspberry Pi 4B, achieving stable tracking at 20–25 FPS
- Applied Kalman filtering on 33 body landmark coordinates for smooth servo motor movement, eliminating chatter from frame-to-frame jitter in joint angle estimates
- Optimized inference using ONNX Runtime for faster CPU execution and improved real-time robotics performance
- Integrated offline Speech-to-Text and NLP-based voice + gesture interaction for multimodal robot control
ML Engineer - Codify Software Services - AWS
(2023-04 - 2024-03)
Bank Customer Churn Prediction
- Trained churn prediction models using Random Forest, Logistic Regression, and LinearSVC on large scale banking data (~2M records), achieving ROC-AUC of ~0.85
- Engineered customer behavioural features including RFM patterns (recency, frequency, monetary), tenure, digital engagement score, and complaint frequency to improve prediction performance
- Applied SMOTE and hyperparameter tuning to improve model stability and generalization.
- Extracted customer data from banking databases using SQL pipelines and stored processed datasets in S3 for ML training workflows.
- Built FastAPI inference APIs and deployed prediction services using Docker and AWS Lambda.
- Used MLflow for experiment tracking, model versioning, and performance comparison across training runs.
Graduate Research Trainee - SAMEER — IIT Bombay
(2019-02 - 2020-02)
Retinal OCT Image Analysis Medical Imaging Research
- Assisted in a 10-year OCT research program; collected raw spectrometer signals from SD-OCT device across multiple retinal tissue samples provided by the research team
- Built Python preprocessing pipelines for raw OCT scan data including Gaussian denoising, CLAHE contrast enhancement, and image normalization to prepare clean 2D B-scan images for analysis
- Applied supervised ML models (Random Forest, SVM) on extracted image features from 2D B-scans to classify retinal conditions; improved ROC-AUC from ~0.65 to ~0.80–0.85 through iterative feature selection and class balancing
- model performance using ROC-AUC, sensitivity, and specificity metrics; plotted results using Matplotlib for research team review
