Machine Learning Engineer
Oracle | Aug 2026 – Present | Contract
- Built a hybrid search pipeline combining dense retrieval via Oracle AI Vector Search and BM25 sparse search
- Fused via Reciprocal Rank Fusion, improving Recall@20 by 26% over the keyword-only baseline
- Fine-tuned MonoBERT re-ranker on 200K query-click pairs for top-50 candidate reordering
- Improved MRR by 18% over the fused retrieval baseline
- Implemented query normalization for noisy and verbose inputs
- Reduced zero-result rate from 7.2% to 3.1% across 30K daily queries
- Evaluated retrieval quality using Recall, NDCG on a 3K human-ranked judgments
- Weekly regression benchmarks tracked via MLflow
- Deployed via FastAPI with Kubernetes and Redis caching
- First-stage retrieval for p99 latency under 80ms
Graduate Researcher
Cisco | Jan 2025 – Jul 2025 | Amherst, MA
- Built PerFine, an Agentic RAG framework for LLM personalization using LangChain
- Graph-based retrieval with Pinecone, FAISS, MCP for profile-grounded feedback
- 13% improvement in personalization, 10% in Meteor score over baselines
- Evaluated using LLM-as-a-Judge (G-Eval) on Yelp, Goodreads, Amazon datasets
Research Assistant
UMass IESL Lab | Aug 2024 – Dec 2024 | Amherst, MA
- Research under Prof. Andrew McCallum
- Built autoregressive model with lookahead decoding in superposition
- Efficient token search using just two forward passes with cross attention
- 15% improvement in BLEU score for MT5 machine translation
Data Scientist
Carelon Global Solutions (Elevance Health) | Jun 2021 – Jul 2023 | Hyderabad, India
Conversational AI System:
- Conversational AI bot with DistilBERT for intent classification & BERT QA for extractive question-answering
- Integrated RAG from S3 on SageMaker, Kubeflow; resolved 65% of patient queries across 1000+ daily interactions
Smart Recommendation Engine:
- Built healthcare recommendation systems using NER, SpaCy, XGBoost, LightGBM in PySpark
- 75% improvement in NDCG@5 for care plan recommendations
- REST APIs with Flask, Hive, MongoDB, Redis for end-to-end model automation
- Reduced care plan creation by ~2 hours through automated recommendations
- Created Splunk Dashboard for tracking KPIs from the user feedback
- Performed A/B testing with feedback-based model tuning drove 60% performance improvement
Sentiment Analysis Pipeline:
- Implemented Aspect-Based Sentiment Analysis on call transcripts using RoBERTa, SpaCy
- Provided actionable insights on patient satisfaction with 85% accuracy, 0.81 F1-score
Healthcare Knowledge Platform:
- Web-scraped healthcare articles indexed in Elasticsearch with ranking optimization; ~120ms retrieval
- Reduced information search time by 90%, enabling faster access to medical guidelines and policies
Production ML Infrastructure:
- Deployed to ENSO ML pipeline using RabbitMQ, Kubernetes, Kafka
- 70% reduction in deployment time via CI/CD pipelines
- Lambda functions for IBM to S3 to DynamoDB pipeline via AWS Glue
- ETL with Google Cloud Vertex AI, Airflow, Docker
AI Engineer Intern
SensorDrops Networks (STEP at IIT Kharagpur) | Aug 2020 – Sep 2020
- Real-time social distance monitoring during COVID using YOLOv3
- 90% detection accuracy with live video feed and bounding boxes
- Deployed on AWS EC2 with Docker, ~200ms latency
- Web interface for 4-camera live streaming with daily/weekly/monthly metrics
AI Engineer Intern
C-DAC, Pune | May 2020 – Aug 2020
- Deep CNN for COVID chest X-ray classification
- 92% accuracy on 3-class classification (COVID, non-COVID, normal)
- F1-score of 0.9 on HPC infrastructure
- CNN-based semi-supervised learning with VOS/VOT improvements