Senior AI/ML Engineer at Nomi Health

Led the development of a major high-impact, LLM-based Generative AI platform using GPT-3.5, FLAN-T5, and Vertex AI to automate federal healthcare policy analysis. Built multimodal document ingestion, semantic search, and summarization, reducing manual review time by 56% over 100K+ documents and enabling real-time responses during the COVID-19 pandemic. Implemented a RAG pipeline with LangChain, FAISS, and Sentence Transformers for real-time semantic search, improving retrieval accuracy by 30% and reducing hallucination errors by 22%. Developed a multimodal document understanding framework (Tesseract OCR, OpenCV, LayoutLMv3) to extract and classify structured content from scanned policies, forms, and contracts, improving table/title/annotation detection by 63%. Created voice-enabled interfaces (Whisper, WebSockets) for hands-free clinician workflow accessibility. Explored agentic reasoning for clinical escalation and triage, achieving a 30% reduction in nurse intervention calls. Impleme

AI/ML Developer at Boston Consulting Group

Designed and implemented scalable, secure AI-driven software solutions for large financial institutions, focusing on fraud detection, anomaly detection, and credit risk modeling. Led MLOps for deploying LLMs (GPT, BERT) for regulatory document parsing and NLG, building an ecosystem with TensorFlow and Hugging Face Transformers for fine-tuning on proprietary financial data. Built domain-specific NLP constructs (intelligent chatbots, virtual financial advisers, knowledge retrieval) and integrated them with secure back-end platforms. Performed extensive EDA on transactional data and developed dynamic visualizations to illustrate fraud trends and customer segments, improving detection response speed by 35%. Implemented interpretability and fairness analyses (SHAP, LIME) for regulatory compliance.

Software Developer at Tango Analytics

Participated in building web and mobile apps with Python, Java, JavaScript; enhanced OpenCV routines to improve model training and inference efficiency; developed full-stack web apps using Django/Flask and React; created RESTful APIs for integrations; optimized real-time data pipelines using AWS and Apache Kafka to boost processing throughput by 30%.

Senior AI/ML Engineer at Nomi Health

Led the development of an LLM-based Generative AI platform using GPT-3.5, FLAN-T5, and Vertex AI to automate federal healthcare policy analysis. Built multimodal document ingestion, semantic search, and summarization workflows, reducing manual review time by 56% across 100K+ documents and enabling real-time responses during the COVID-19 pandemic. Designed a RAG pipeline with LangChain, FAISS, and Sentence Transformers to improve retrieval accuracy and reduce hallucinations. Created a multimodal content extraction framework (OCR/OpenCV/LayoutLMv3) and voice-enabled interfaces for clinician workflows, enabling hands-free operations. Implemented asynchronous FastAPI microservices, AWS Lambda/EC2 integration, and FedRAMP-compliant AWS infrastructure, with MLflow/W&B tracking and governance to ensure compliance and auditability.

AI/ML Developer at Boston Consulting Group

Designed scalable AI-driven software for large financial institutions, focusing on fraud detection, transaction anomaly detection, and credit risk modeling. Built LLM-based document classification and NLG using TensorFlow and Hugging Face Transformers; developed domain-specific NLP tools (intelligent chatbots, virtual advisers, knowledge retrieval) and secure Django back-end integration. Conducted exploratory data analysis and delivered insights that improved fraud detection response time by 35%.

Software Developer at Tango Analytics

Participated in full-stack web/mobile application development using Python, Java, JavaScript, Django, Flask, React, and MongoDB. Enhanced OpenCV-based image processing to improve model training and inference efficiency, built scalable RESTful APIs, and optimized real-time data pipelines with AWS and Kafka to boost processing throughput by ~30%.

Senior AI/ML Engineer at Nomi Health

Led the development of a major LLM-based Generative AI platform to automate federal healthcare policy analysis using GPT-3.5, FLAN-T5, and Vertex AI. Built multimodal document ingestion, semantic search, and summarization, reducing manual review time by 56% across 100K+ documents and enabling real-time responses during the COVID-19 pandemic. Designed a RAG pipeline with LangChain, FAISS, and Sentence Transformers for real-time semantic search, improving retrieval accuracy by 30% and reducing hallucinations by 22%. Implemented a multimodal document understanding framework using Tesseract OCR, OpenCV, and LayoutLMv3, increasing detection of tables and content structure by 63%. Created voice-enabled interfaces (Whisper, WebSockets) for hands-free clinician workflows, improving adoption. Prototyped agentic reasoning systems for clinical escalation and triage via LangGraph, achieving a 30% reduction in nurse interventions during peak operations. Developed domain-adapted prompt templates for

AI/ML Developer at Boston Consulting Group

Designed scalable, secure AI-driven software for large financial institutions focused on fraud detection, transaction anomaly detection, and credit risk modeling. Led MLOps for deploying state-of-the-art LLMs (GPT, BERT) for financial document classification, regulatory document parsing, and natural language generation, building a deep learning ecosystem with TensorFlow and Hugging Face Transformers for fine-tuning on proprietary datasets. Developed domain-specific NLP constructs such as intelligent chatbots, virtual financial advisers, and internal knowledge retrieval systems; integrated development APIs with Django for secure banking platform integrations. Conducted EDA on transactional, behavioral, and demographic data using pandas, NumPy, SQL, DataBricks, and GCP AI services to identify risk factors. Built dynamic visualizations with Matplotlib, Seaborn, and Plotly to illustrate fraud trends and segmentation, enabling faster detection by 35%. Implemented supervised and unsupervised

Software Developer at Tango Analytics

Contributed to scalable web and mobile apps using Python, Java, and JavaScript. Built maintainable web applications with TensorFlow, PyTorch, Django, Flask, React, and MongoDB. Enhanced OpenCV-based image processing to accelerate model training and inference, reducing costs by over 15%. Developed RESTful APIs for secure, scalable integrations and leveraged AWS and Apache Kafka to optimize real-time data pipelines, increasing processing throughput by 30%.

Senior AI/ML Engineer at Nomi Health

Led the development of a major high-impact, LLM-based Generative AI platform using GPT-3.5, FLAN-T5, and Vertex AI to automate federal healthcare policy analysis. Built multimodal document ingestion, semantic search, and summarization pipelines processing 100K+ documents, reducing manual review time by 56% and enabling real-time responses during the COVID-19 emergency. Designed a retrieval-augmented generation (RAG) framework with LangChain, FAISS, and Sentence Transformers to enable real-time semantic search, increasing retrieval accuracy by 30% and reducing hallucination-related errors by 22%. Implemented a multimodal document understanding framework using Tesseract OCR, OpenCV, and LayoutLMv3 to extract and classify content from scanned policies, forms, and contracts, improving table and annotation detection by 63%. Developed hands-free clinician interfaces via Whisper and WebSockets, enabling easier clinician workflow. Prototyped agentic reasoning systems for clinical escalation an

AI/ML Developer at Boston Consulting Group

Designed scalable, secure AI-driven software for large financial institutions with a focus on fraud detection, transaction anomaly detection, and credit risk modeling. Led MLOps and deployments for state-of-the-art LLMs (GPT, BERT) for regulatory document classification and natural language generation, building a deep learning ecosystem with TensorFlow and Hugging Face Transformers. Performed extensive EDA on transactional, behavioral, and demographic data to guide model selection, manipulating structured and semi-structured data with Pandas, NumPy, SQL, DataBricks, and GCP AI services. Built interoperable visualizations to illustrate fraud trends and loan default risk, delivering actionable insights that improved detection speed. Integrated model outputs with secure APIs and legacy banking systems, including Django-based back-end support and user-facing interfaces. Conducted interpretability and fairness analyses with SHAP/LIME to support Basel III and GDPR compliance and ensured audi

Software Developer at Tango Analytics

Participated in the creation of scalable web and mobile applications using Python, Java, JavaScript, Django, Flask, React, and MongoDB. Optimized OpenCV image processing routines to accelerate model training and inference, reducing costs by over 15%. Contributed to full-stack development including RESTful API design, cloud deployments, and real-time data pipelines with AWS and Apache Kafka, enabling a 30% improvement in data throughput. Supported secure, scalable deployments and cross-team collaboration across data engineering and cloud infrastructure.

Senior AI/ML Engineer at Nomi Health

Led the development of a major LLM-based Generative AI platform using GPT-3.5, FLAN-T5, and Vertex AI to automate federal healthcare policy analysis. Built multimodal document ingestion, semantic search, and summarization for 100K+ documents, enabling real-time responses during healthcare emergencies. Implemented a retrieval-augmented generation (RAG) pipeline with LangChain, FAISS, and Sentence Transformers to improve retrieval accuracy and reduce hallucinations. Developed a multimodal document understanding framework using Tesseract OCR, OpenCV, and LayoutLMv3 to extract and classify content from scanned policies, forms, and contracts, improving table and layout detection.

AI/ML Developer at Boston Consulting Group

Designed and implemented Fintron’s scalable AI-driven software solutions for large financial institutions focusing on fraud detection, transaction anomaly detection, and credit risk modeling. Led MLOps for deploying state-of-the-art LLMs for financial document classification, regulatory document parsing, and natural language generation. Built a deep learning ecosystem using TensorFlow and Hugging Face Transformers to fine-tune LLMs on proprietary financial datasets, and developed domain-specific NLP constructs and retrieval systems.

Software Developer at Tango Analytics

Participated in the creation of scalable web applications, leveraging TensorFlow, PyTorch, Django, Flask, and React. Enhanced OpenCV image processing routines to improve model training and inference efficiency, built RESTful APIs for secure integrations, and optimized real-time data pipelines with AWS and Apache Kafka to increase data processing throughput by ~30%.

Senior AI/ML Engineer at Nomi Health

Led the development of a FedRAMP-compliant, LLM-driven Generative AI platform (GPT-3.5, FLAN-T5, Vertex AI) for automating federal healthcare policy analysis. Architected multimodal document ingestion, semantic search, and summarization pipelines; delivered faster reviews, improved retrieval accuracy, and reduced hallucinations. Built OCR-based content extraction with LayoutLMv3; developed voice-enabled clinician interfaces; prototyped agentic reasoning for triage; implemented governance, monitoring, and reproducibility pipelines; ensured HIPAA/HHS compliance and secure, scalable cloud infrastructure.

AI/ML Developer at Boston Consulting Group

Designed scalable AI-driven solutions for fraud detection, transaction anomaly detection, and credit risk modeling for large financial institutions. Led MLOps for deploying LLMs for document classification, regulatory parsing, and natural language generation; built a deep learning ecosystem with TensorFlow and HuggingFace Transformers to fine-tune state-of-the-art LLMs on proprietary financial documents. Developed domain-specific NLP constructs such as intelligent chatbots and knowledge retrieval systems; performed EDA and created visualizations to illustrate fraud trends and loan defaults; delivered improved detection speed and regulatory explainability; ensured compliance with Basel III and GDPR.