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Sr. AI/ML engineer with 10+ years of experience building, deploying, and fine-tuning NLP and generative AI/LLM solutions (GPT/BERT, RAG, agents) across healthcare and enterprise environments. Strong Python expertise and hands-on delivery of production-grade AI systems using PyTorch, TensorFlow, Hugging Face, and LangChain/Llama/LlamaIndex. Experienced in MLOps and cloud-native deployments across AWS, Azure, and GCP, including CI/CD with Docker and Kubernetes, model lifecycle automation, monitoring, and secure HIPAA-aligned implementations. Led multiple end-to-end initiatives including sentiment analysis, enterprise copilots, forecasting, and knowledge graph/RAG systems with measurable improvements in efficiency and customer outcomes.…Sr. AI/ML engineer with 10+ years of experience building, deploying, and fine-tuning NLP and generative AI/LLM solutions (GPT/BERT, RAG, agents) across healthcare and enterprise environments. Strong Python expertise and hands-on delivery of production-grade AI systems using PyTorch, TensorFlow, Hugging Face, and LangChain/Llama/LlamaIndex. Experienced in MLOps and cloud-native deployments across AWS, Azure, and GCP, including CI/CD with Docker and Kubernetes, model lifecycle automation, monitoring, and secure HIPAA-aligned implementations. Led multiple end-to-end initiatives including sentiment analysis, enterprise copilots, forecasting, and knowledge graph/RAG systems with measurable improvements in efficiency and customer outcomes.

Rajesh Adhi

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Sr. AI/ML engineer with 10+ years of experience building, deploying, and fine-tuning NLP and generative AI/LLM solutions (GPT/BERT, RAG, agents) across healthcare and enterprise environments. Strong Python expertise and hands-on delivery of production-grade AI systems using PyTorch, TensorFlow, Hugging Face, and LangChain/Llama/LlamaIndex. Experienced in MLOps and cloud-native deployments across AWS, Azure, and GCP, including CI/CD with Docker and Kubernetes, model lifecycle automation, monitoring, and secure HIPAA-aligned implementations. Led multiple end-to-end initiatives including sentiment analysis, enterprise copilots, forecasting, and knowledge graph/RAG systems with measurable improvements in efficiency and customer outcomes.…Sr. AI/ML engineer with 10+ years of experience building, deploying, and fine-tuning NLP and generative AI/LLM solutions (GPT/BERT, RAG, agents) across healthcare and enterprise environments. Strong Python expertise and hands-on delivery of production-grade AI systems using PyTorch, TensorFlow, Hugging Face, and LangChain/Llama/LlamaIndex. Experienced in MLOps and cloud-native deployments across AWS, Azure, and GCP, including CI/CD with Docker and Kubernetes, model lifecycle automation, monitoring, and secure HIPAA-aligned implementations. Led multiple end-to-end initiatives including sentiment analysis, enterprise copilots, forecasting, and knowledge graph/RAG systems with measurable improvements in efficiency and customer outcomes.

Available to hire

Sr. AI/ML engineer with 10+ years of experience building, deploying, and fine-tuning NLP and generative AI/LLM solutions (GPT/BERT, RAG, agents) across healthcare and enterprise environments. Strong Python expertise and hands-on delivery of production-grade AI systems using PyTorch, TensorFlow, Hugging Face, and LangChain/Llama/LlamaIndex.

Experienced in MLOps and cloud-native deployments across AWS, Azure, and GCP, including CI/CD with Docker and Kubernetes, model lifecycle automation, monitoring, and secure HIPAA-aligned implementations. Led multiple end-to-end initiatives including sentiment analysis, enterprise copilots, forecasting, and knowledge graph/RAG systems with measurable improvements in efficiency and customer outcomes.

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Work Experience

Sr. Gen AI Engineer at Massachusetts General Hospital

December 1, 2024 - Present

Designed, tested, fine-tuned, and deployed GenAI/LLM solutions (GPT/BERT, chatbots, summarization, assistants) and built enterprise copilots. Implemented RAG systems using LangChain and LlamaIndex for document ingestion, indexing, retrieval, and response generation, integrating vector databases and domain-specific knowledge bases. Built agentic workflows with LangGraph/CrewAI/AutoGen including tool calling, conditional routing, multi-step planning, and human-in-the-loop approvals. Developed and integrated REST APIs connecting LLM outputs to downstream apps, and implemented secure, context-aware conversational AI using Semantic Kernel with Azure OpenAI and Retrieval-Augmented Generation. Deployed solutions on AWS (Bedrock) and GCP (Vertex AI), implemented LLM evaluation and monitoring, and automated model/prompt deployment pipelines with MLflow, GitHub Actions, Docker, and Kubernetes. Built multimodal document processing workflows using OCR and vision-language approaches where needed, w

Sr. AI/ML Engineer at AT&T

May 1, 2023 - October 1, 2024

Architected cloud-native ML pipelines using SageMaker Pipelines, Argo Workflows, and Apache Airflow for scalable, reproducible training/validation/deployment. Built centralized feature infrastructure using Feast with real-time and batch serving for epidemiological models. Implemented autonomous multi-agent applications using Microsoft AutoGen, and engineered containerized inference environments using Docker with serving through Triton Inference Server and TensorFlow Serving on Amazon EKS. Standardized deployment with Terraform/Helm/Kustomize and secrets management via Vault. Developed low-latency secured APIs using FastAPI (OAuth2, AWS Secrets Manager), automated dataset/version/artifact governance with DVC and GitOps, and operationalized monitoring via CloudWatch Logs Insights. Implemented explainability reporting using SHAP/LIME and built RAG pipelines using FAISS/Pinecone for network risk analytics. Fine-tuned models with LoRA for anomaly detection workflows and implemented dynamic

Data Scientist at Morgan Stanley

May 1, 2020 - February 1, 2023

Worked on predictive modeling and applied ML techniques to complex enterprise datasets, including imbalanced fraud detection and operational analytics. Built knowledge graph solutions with Neo4j to support semantic search, contextual reasoning, and enterprise knowledge discovery. Developed predictive maintenance and asset monitoring solutions. Implemented large-scale data analytics with SparkSQL and AWS Spark/MapReduce; performed data cleaning and preprocessing using Pandas/NumPy. Designed graph data models and Cypher queries for relationship traversal and semantic retrieval. Improved fraud detection using feature selection (Random Forest, Gradient Boosting) and built supervised models (Naive Bayes, KNN, Logistic Regression, SVM, Random Forest, XGBoost). Integrated Neo4j with LangChain and vector databases to enhance RAG/enterprise search and retrieval. Evaluated models using ROC/AUC, F1, MAE/RMSE. Delivered dashboards and analytics via Tableau after integrating and blending data using

Data Scientist at State Farm Insurance

September 1, 2018 - April 1, 2020

Designed ML pipelines with DVC and Git for dataset versioning, feature engineering, and model checkpointing. Implemented experiment tracking and lineage with MLflow for auditable model comparison. Deployed ML models via AWS SageMaker Inference Endpoints and supported A/B testing and production rollouts. Automated training and release workflows using GitHub Actions, containerized with Docker, and deployed to Kubernetes for reproducible environments. Implemented RAG and vector database approaches for risk/compliance knowledge retrieval and applied LoRA fine-tuning to accelerate iterations. Built secure inference and monitoring APIs using FastAPI. Integrated enterprise workflows with SAP and IBM Maximo through REST APIs to automate maintenance planning, asset management, and reporting. Developed monitoring scripts for data drift/inference anomalies and maintained reproducible notebooks and governance-aligned CI workflows.

Sr. Data Analyst at Apple

November 1, 2016 - August 1, 2018

Performed data analysis, migration, preparation, and ETL pipeline development for customer segmentation and profiling. Implemented investigation calculations and data validation scripts in Python using Pandas/NumPy/Seaborn/SciPy/Matplotlib and scikit-learn, including NLTK-based work. Built and optimized ETL processes (Alteryx to Snowflake) and developed statistical and pricing analyses. Created visual KPI dashboards and reports in Tableau and supported live interactive Tableau server publishing with extracts and refresh automation. Managed GIT repositories and access control strategies for multiple projects. Worked extensively with ER/Studio for OLAP/OLTP data modeling and produced ad-hoc SQL queries across Oracle and SQL Server environments. Contributed to UI/UX e-learning application development using jQuery/JavaScript/HTML/NodeJS and supported data-driven dashboarding for learning content.

Data Analyst at Aldi’s

August 1, 2014 - October 1, 2016

Translated stakeholder business and application requirements into data models supporting standardized pipeline practices. Extracted historical and real-time data using Hive/MapReduce/HDFS in Hadoop ecosystems and implemented Hive UDFs for advanced string/date/data manipulation. Performed data cleaning, scaling, and feature engineering using Pandas/NumPy. Applied clustering (K-Means, hierarchical clustering) to support segmentation. Presented insights to executives and built interactive Tableau reports with calculated fields, parameters, filters, sets/groups, and advanced visualization types. Published workbooks/extracts to Tableau Server with row-level security and scheduled refreshes for operational reporting.