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I am an AI/ML Engineer with 6+ years of experience designing and deploying intelligent automation, predictive analytics, and LLM-powered solutions across healthcare, finance, and enterprise IT. I thrive on building scalable MLOps workflows, leveraging Python, FastAPI, and cloud platforms like AWS SageMaker and Azure ML to turn data into measurable business impact. Passionate about simplifying operations and enhancing decision-making, I enjoy translating complex data science into practical, maintainable systems that drive real-world outcomes.…I am an AI/ML Engineer with 6+ years of experience designing and deploying intelligent automation, predictive analytics, and LLM-powered solutions across healthcare, finance, and enterprise IT. I thrive on building scalable MLOps workflows, leveraging Python, FastAPI, and cloud platforms like AWS SageMaker and Azure ML to turn data into measurable business impact. Passionate about simplifying operations and enhancing decision-making, I enjoy translating complex data science into practical, maintainable systems that drive real-world outcomes.

Sekhar A

AI Engineer, Developer, Data Scientist, +4

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I am an AI/ML Engineer with 6+ years of experience designing and deploying intelligent automation, predictive analytics, and LLM-powered solutions across healthcare, finance, and enterprise IT. I thrive on building scalable MLOps workflows, leveraging Python, FastAPI, and cloud platforms like AWS SageMaker and Azure ML to turn data into measurable business impact. Passionate about simplifying operations and enhancing decision-making, I enjoy translating complex data science into practical, maintainable systems that drive real-world outcomes.…I am an AI/ML Engineer with 6+ years of experience designing and deploying intelligent automation, predictive analytics, and LLM-powered solutions across healthcare, finance, and enterprise IT. I thrive on building scalable MLOps workflows, leveraging Python, FastAPI, and cloud platforms like AWS SageMaker and Azure ML to turn data into measurable business impact. Passionate about simplifying operations and enhancing decision-making, I enjoy translating complex data science into practical, maintainable systems that drive real-world outcomes.

Available to hire

I am an AI/ML Engineer with 6+ years of experience designing and deploying intelligent automation, predictive analytics, and LLM-powered solutions across healthcare, finance, and enterprise IT. I thrive on building scalable MLOps workflows, leveraging Python, FastAPI, and cloud platforms like AWS SageMaker and Azure ML to turn data into measurable business impact.

Passionate about simplifying operations and enhancing decision-making, I enjoy translating complex data science into practical, maintainable systems that drive real-world outcomes.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

AI/ML Engineer at MXT Groups

June 1, 2024 - Present

Led the design and deployment of an AI-powered Automation Copilot for enterprise IT operations that enabled chat-driven workflow automation using LLMs, RAG pipelines, and AWS cloud services. Automated incident triage, form filling, and RPA triggers, increasing IT resolution time by 55% and adoption across 6+ departments. Integrated the Copilot with ServiceNow, internal web applications, and secure APIs while implementing MLOps best practices including CI/CD pipelines, monitoring, and governance controls. Utilized LangChain, LangGraph, Pinecone, FastAPI, AWS SageMaker, and Kubernetes technologies to build scalable and secure AI solutions.

ML Engineer at Medica

May 31, 2023 - September 4, 2025

Developed and deployed a LightGBM predictive analytics model for disease risk stratification on EHR data achieving over 90% AUC. Implemented explainable AI using SHAP and LIME for clinician insights to support real-time decision making. Containerized and orchestrated ML services on Azure Kubernetes Service, leveraging Azure Databricks for large-scale EHR processing. Ensured HIPAA compliance, operational adoption, and clinical alignment through collaborations with healthcare professionals. Used Azure ML for experiment tracking, automated retraining, and production deployment.

Python Developer at GlobalLogic

January 31, 2021 - September 4, 2025

Designed and maintained backend services, data pipelines, and analytics dashboards for financial data processing and reporting. Developed RESTful APIs using Django REST Framework and Flask, automated ETL pipelines, and integrated real-time market data APIs improving analyst decision accuracy. Built interactive visualizations and ensured high quality through rigorous testing and CI/CD deployments using Jenkins and Docker. Collaborated in Agile teams with strong version control practices.

AI/ML Engineer at Automation Anywhere (MXT Groups)

June 1, 2024 - November 12, 2025

Designed and deployed an AI-powered Copilot using LLMs, LangChain, LangGraph and AWS SageMaker to automate IT workflows, incident triage, and RPA-driven tasks, reducing resolution time by 55% across 6+ departments. Integrated the Copilot with ServiceNow and internal tools via secure REST APIs, enabling chat-driven automation, form filling, and triggering 200+ daily RPA workflows. Built RAG pipelines with Pinecone to semantically retrieve 10,000+ enterprise documents and support tickets with 85% accuracy and 78%+ answer relevance, ensuring real-time knowledge access. Developed multi-step orchestration flows using LangChain and LangGraph for contextual task execution, while implementing MLOps pipelines with MLflow, FastAPI, and GitHub Actions for CI/CD, drift monitoring, and experiment tracking. Ensured end-to-end security and compliance with JWT authentication, OAuth2, RBAC, and audit logging across all API layers, while monitoring Copilot performance using Prometheus and Grafana.

ML Engineer at Medica

May 31, 2023 - May 31, 2023

Built and deployed end-to-end ML systems for real-time patient disease risk prediction, achieving >90% AUC, and enabling clinicians to evaluate 100+ patients daily with actionable insights. Designed and optimized distributed data pipelines on Azure Databricks to process multi-million record EHR datasets, improving data quality, feature extraction, and training efficiency by 40%+. Operationalized ML models via Flask REST APIs on Azure App Service, integrating predictions directly into hospital dashboards to automate alerts and support timely clinical decisions. Implemented MLOps workflows with Azure ML, MLflow, Docker, and AKS, enabling version control, automated retraining, containerized deployment, and reducing production downtime by 30%. Enhanced model transparency and adoption through SHAP-based explainability, ensuring clinicians could interpret predictions confidently, while maintaining HIPAA-compliant pipelines for secure data handling.

Python Developer at GlobalLogic

January 31, 2021 - January 31, 2021

Developed scalable backend services using Django REST Framework and Flask, enabling secure processing of financial transactions and providing real-time data access for internal reporting dashboards. Automated high-volume ETL data pipelines for CSV, Excel, and API sources, reducing manual processing by 70% and ensuring timely availability of clean datasets for analytics. Built interactive KPI dashboards with Plotly and Matplotlib, allowing stakeholders to visualize trends, detect anomalies, and track performance metrics efficiently. Improved code quality, deployment, and system reliability through PyTest-based testing (90% coverage), CI/CD with Jenkins and Docker, optimized PostgreSQL queries, and structured logging, reducing errors and downtime by 40%.