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I am Chandrika Chandra, an AI/ML Engineer who thrives on turning complex data into scalable, production-ready solutions. I design and deploy end-to-end ML pipelines on AWS and cloud-native platforms, collaborating with cross-functional teams to deliver measurable impact in healthcare, fintech, and enterprise software. I enjoy embracing MLOps best practices, automating workflows, and continuously learning about new AI techniques to improve model reliability, fairness, and performance while communicating insights through clear visualizations.…I am Chandrika Chandra, an AI/ML Engineer who thrives on turning complex data into scalable, production-ready solutions. I design and deploy end-to-end ML pipelines on AWS and cloud-native platforms, collaborating with cross-functional teams to deliver measurable impact in healthcare, fintech, and enterprise software. I enjoy embracing MLOps best practices, automating workflows, and continuously learning about new AI techniques to improve model reliability, fairness, and performance while communicating insights through clear visualizations.

Chandrika Chandra

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

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I am Chandrika Chandra, an AI/ML Engineer who thrives on turning complex data into scalable, production-ready solutions. I design and deploy end-to-end ML pipelines on AWS and cloud-native platforms, collaborating with cross-functional teams to deliver measurable impact in healthcare, fintech, and enterprise software. I enjoy embracing MLOps best practices, automating workflows, and continuously learning about new AI techniques to improve model reliability, fairness, and performance while communicating insights through clear visualizations.…I am Chandrika Chandra, an AI/ML Engineer who thrives on turning complex data into scalable, production-ready solutions. I design and deploy end-to-end ML pipelines on AWS and cloud-native platforms, collaborating with cross-functional teams to deliver measurable impact in healthcare, fintech, and enterprise software. I enjoy embracing MLOps best practices, automating workflows, and continuously learning about new AI techniques to improve model reliability, fairness, and performance while communicating insights through clear visualizations.

Available to hire

I am Chandrika Chandra, an AI/ML Engineer who thrives on turning complex data into scalable, production-ready solutions. I design and deploy end-to-end ML pipelines on AWS and cloud-native platforms, collaborating with cross-functional teams to deliver measurable impact in healthcare, fintech, and enterprise software.

I enjoy embracing MLOps best practices, automating workflows, and continuously learning about new AI techniques to improve model reliability, fairness, and performance while communicating insights through clear visualizations.

Skills

Experience Level

Expert

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Intermediate

Work Experience

AI/ML Engineer at Emory Healthcare

June 1, 2025 - Present

Identify, gather, and analyse complex, multi-dimensional datasets from diverse sources to support clinical and operational analytics. Build and optimize end-to-end ML pipelines (data ingestion, feature engineering, model training, and real-time/batch inference). Deploy AWS SageMaker endpoints and Lambda-triggered workflows for scalable inference. Collaborate with data engineers to merge data from Snowflake, PostgreSQL, and NoSQL sources, ensuring data quality and lineage. Monitor production ML workloads via CloudWatch and dashboards; implement drift detection and alerting to minimize downtime. Develop visualizations in Tableau/Seaborn to communicate insights to clinical and administrative stakeholders. Lead MLOps efforts, including versioning, experiment tracking with MLflow, automated testing, and CI/CD for rapid yet reliable iterations.

AI/ML Engineer at Intuit

October 1, 2024 - May 31, 2025

Collaborated with management to prioritize business needs and align ML initiatives with sales objectives. Implemented computer vision for packaging defect detection using OpenCV; trained a PyTorch model to classify packaging as defective. Built an LLM-powered tool to summarize long reports for provider hand-off. Engineered a dynamic pricing model using SageMaker and XGBoost to optimize prices based on inventory, competition, and demand elasticity. Pre-processed data with AWS Glue/EMR, performed performance evaluations, and integrated ML outputs into business workflows.

Software Engineer at Wipro

May 1, 2022 - January 31, 2023

Designed and deployed scalable predictive models for customer churn and risk scoring, leveraging Azure ML pipelines. Automated ETL + ML workflows in Azure Data Factory, integrating diverse structured and unstructured data sources. Deployed ML models as REST APIs (Flask/Azure Functions), enabling real-time inference. Implemented monitoring and drift detection to improve model reliability and fairness; developed reusable Python packages for feature engineering and model evaluation; mentored junior engineers on MLOps practices; built PySpark feature pipelines for telemetry data; applied ARIMA/Prophet time-series forecasting for demand planning; automated data validation and unit testing; transitioned research prototypes to production; integrated Power BI dashboards for ML-driven insights.

Python Developer at HCL – Hyderabad

February 1, 2021 - April 30, 2022

Gained requirement clarity and authored maintenance documentation; developed Python components using Django; designed backend and frontend portions; created a Django dashboard with custom UI; built interactive frontend with HTML/CSS/JavaScript/jQuery; implemented AWS Lambda-driven event processing; configured Jenkins CI/CD and version control; migrated databases (SQLite -> MySQL -> PostgreSQL) with data integrity; generated graphical reports with NumPy/Matplotlib; deployed projects via Git, GitHub integration; conducted unit testing and ensured reliable deployment and monitoring practices.