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Senior AI/ML engineer with 10 years of enterprise-scale experience delivering predictive modeling, deep learning, NLP, and generative AI solutions. Hands-on building and deploying production ML systems using AWS SageMaker, Azure ML, and Google Cloud AI, with strong MLOps, CI/CD, and scalable architecture experience. Expert in LLM-based platforms, RAG, and agentic workflows (tool/function calling, ReAct, memory-enabled and multi-agent collaboration). Proven ability to translate complex business requirements into measurable outcomes while ensuring security, governance, monitoring, and model reliability in production environments.…Senior AI/ML engineer with 10 years of enterprise-scale experience delivering predictive modeling, deep learning, NLP, and generative AI solutions. Hands-on building and deploying production ML systems using AWS SageMaker, Azure ML, and Google Cloud AI, with strong MLOps, CI/CD, and scalable architecture experience. Expert in LLM-based platforms, RAG, and agentic workflows (tool/function calling, ReAct, memory-enabled and multi-agent collaboration). Proven ability to translate complex business requirements into measurable outcomes while ensuring security, governance, monitoring, and model reliability in production environments.

user1784754

AI Engineer, Data Engineer, Full Stack Developer, +2

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Senior AI/ML engineer with 10 years of enterprise-scale experience delivering predictive modeling, deep learning, NLP, and generative AI solutions. Hands-on building and deploying production ML systems using AWS SageMaker, Azure ML, and Google Cloud AI, with strong MLOps, CI/CD, and scalable architecture experience. Expert in LLM-based platforms, RAG, and agentic workflows (tool/function calling, ReAct, memory-enabled and multi-agent collaboration). Proven ability to translate complex business requirements into measurable outcomes while ensuring security, governance, monitoring, and model reliability in production environments.…Senior AI/ML engineer with 10 years of enterprise-scale experience delivering predictive modeling, deep learning, NLP, and generative AI solutions. Hands-on building and deploying production ML systems using AWS SageMaker, Azure ML, and Google Cloud AI, with strong MLOps, CI/CD, and scalable architecture experience. Expert in LLM-based platforms, RAG, and agentic workflows (tool/function calling, ReAct, memory-enabled and multi-agent collaboration). Proven ability to translate complex business requirements into measurable outcomes while ensuring security, governance, monitoring, and model reliability in production environments.

Available to hire

Senior AI/ML engineer with 10 years of enterprise-scale experience delivering predictive modeling, deep learning, NLP, and generative AI solutions. Hands-on building and deploying production ML systems using AWS SageMaker, Azure ML, and Google Cloud AI, with strong MLOps, CI/CD, and scalable architecture experience.

Expert in LLM-based platforms, RAG, and agentic workflows (tool/function calling, ReAct, memory-enabled and multi-agent collaboration). Proven ability to translate complex business requirements into measurable outcomes while ensuring security, governance, monitoring, and model reliability in production environments.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Advanced

Work Experience

Senior GenAI/ML Engineer at Capital One

January 1, 2024 - Present

Led enterprise-scale AI/ML solution design and deployment across predictive modeling, NLP, and generative AI. Modernized CI/CD workflows by migrating legacy Jenkins pipelines to GitHub Actions and Tekton with reusable templates, automated testing, security validation, and deployment orchestration. Built enterprise engineering dashboards using Power BI to track DORA metrics and delivery/release quality. Designed secure DevSecOps pipelines with GitHub Enterprise governance, branch protection, code quality validation, secret scanning, dependency analysis, OAuth2/JWT authentication, and release management best practices. Implemented real-time ML inference solutions using AWS SageMaker, Azure ML, and Google Cloud AI; optimized hyperparameters, quantization, and distributed compute for lower inference latency. Developed full-stack AI apps using Next.js/React integrated with LLM-backed services. Built agentic and multi-agent orchestration with LangChain/LangGraph, including tool/function call

GenAI/ML Engineer at Relevance Health

November 1, 2021 - December 31, 2023

Designed and implemented generative AI models for document summarization and knowledge extraction, reducing manual review time by 40%. Built secure REST API integrations using OAuth 2.0/JWT and API Gateway for scalable enterprise API governance. Developed internal developer enablement by integrating GitHub Copilot and generative AI coding assistants into engineering workflows to improve code quality and delivery velocity. Built CI/CD automation using GitHub Actions for build/test/artifact packaging/deployment across environments. Built domain-specific LLM solutions leveraging GPT/Transformer architectures for semantic search and improved retrieval accuracy. Implemented RAG pipelines enabling real-time access to relevant documents and improved response times. Engineered reproducible Python-based ML pipelines for ingestion, preprocessing, feature extraction, training, and evaluation. Fine-tuned pre-trained LLMs on domain datasets achieving 85%+ accuracy on targeted NLP tasks. Built multi

Machine Learning Engineer at The Home Depot

August 1, 2019 - October 31, 2021

Designed, developed, and deployed supervised and unsupervised ML models for predictive analytics, classification, and clustering. Built end-to-end ML pipelines including data ingestion, preprocessing, feature engineering, training, validation, and deployment. Developed deep learning models for structured, text, and image data using TensorFlow and PyTorch. Implemented NLP solutions for sentiment analysis, text classification, tokenization, and named entity recognition. Performed hyperparameter tuning, cross-validation, and model evaluation to improve accuracy and reduce overfitting. Implemented agentic AI solutions using Google ADK focused on real-time task execution and tool orchestration. Deployed models on AWS SageMaker, Azure ML, and Google Cloud AI. Built automated data pipelines in Python and SQL reducing manual data preparation by ~40%. Developed Express.js API layers to expose ML/NLP services as scalable microservices for enterprise consumption, integrated front-end interfaces,

Data Scientist at Tatva Soft

May 1, 2015 - December 31, 2018

Developed and deployed predictive models in Python (pandas, NumPy, scikit-learn) and R, improving forecast accuracy by 15% for key business metrics. Conducted data cleaning, preprocessing, and feature engineering on large structured and unstructured datasets, reducing data preparation time by 25%. Built and maintained SQL-based ETL pipelines for extract-transform-load across enterprise systems. Used SQL and Python to extract, manipulate, and analyze datasets and streamline reporting. Implemented supervised and unsupervised ML algorithms (regression, classification, clustering) to generate actionable business insights. Designed and visualized Tableau dashboards for KPI tracking and data-driven decision-making. Developed web-based data science applications using JavaScript and React; built Node.js/Express APIs to serve real-time ML predictions. Performed A/B testing and experiment design, leveraged time-series analysis (ARIMA/Prophet) for demand/sales forecasting, applied NLP methods (te