Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I’m Nipun Muluka, a Full Stack AI Engineer with 10+ years of experience building intelligent applications that blend ML with modern web architectures. I specialize in Python, React, and integrating LLMs with scalable web platforms to deliver AI-powered products. I’ve led end-to-end projects across cloud and containerized environments (AWS, Azure, Docker, Kubernetes) with CI/CD automation. I enjoy turning data into actionable insights, collaborating with cross-functional teams, and translating business goals into practical AI features.…I’m Nipun Muluka, a Full Stack AI Engineer with 10+ years of experience building intelligent applications that blend ML with modern web architectures. I specialize in Python, React, and integrating LLMs with scalable web platforms to deliver AI-powered products. I’ve led end-to-end projects across cloud and containerized environments (AWS, Azure, Docker, Kubernetes) with CI/CD automation. I enjoy turning data into actionable insights, collaborating with cross-functional teams, and translating business goals into practical AI features.

Nipun Muluka

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





I’m Nipun Muluka, a Full Stack AI Engineer with 10+ years of experience building intelligent applications that blend ML with modern web architectures. I specialize in Python, React, and integrating LLMs with scalable web platforms to deliver AI-powered products. I’ve led end-to-end projects across cloud and containerized environments (AWS, Azure, Docker, Kubernetes) with CI/CD automation. I enjoy turning data into actionable insights, collaborating with cross-functional teams, and translating business goals into practical AI features.…I’m Nipun Muluka, a Full Stack AI Engineer with 10+ years of experience building intelligent applications that blend ML with modern web architectures. I specialize in Python, React, and integrating LLMs with scalable web platforms to deliver AI-powered products. I’ve led end-to-end projects across cloud and containerized environments (AWS, Azure, Docker, Kubernetes) with CI/CD automation. I enjoy turning data into actionable insights, collaborating with cross-functional teams, and translating business goals into practical AI features.

Available to hire

I’m Nipun Muluka, a Full Stack AI Engineer with 10+ years of experience building intelligent applications that blend ML with modern web architectures. I specialize in Python, React, and integrating LLMs with scalable web platforms to deliver AI-powered products.

I’ve led end-to-end projects across cloud and containerized environments (AWS, Azure, Docker, Kubernetes) with CI/CD automation. I enjoy turning data into actionable insights, collaborating with cross-functional teams, and translating business goals into practical AI features.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Fluent

Work Experience

Full Stack AI Engineer at Sam's Club

June 1, 2023 - Present

Led full lifecycle of data science initiatives including ML, data acquisition, cleansing, and visualization. Designed and deployed AI-powered web applications integrating a React frontend with a FastAPI Python backend to deliver generative AI insights. Built SQL agents enabling natural language-to-SQL interactions for intuitive database access, and developed REST APIs/microservices connecting LLM outputs to enterprise dashboards. Used AWS services (S3, EC2, Lambda, DynamoDB, Redshift, SageMaker) to manage data storage and deploy scalable ML models. Implemented RAG pipelines with LangChain and vector databases (Pinecone/FAISS) for document retrieval. Modeled analytical data with Snowflake using star and snowflake schemas. Created Power BI dashboards to communicate results. Applied ML techniques including regression, decision trees, random forests, clustering, and dimensionality reduction; trained and deployed models on SageMaker; performed EDA for feature engineering. Collaborated with

AI Engineer at Molina Healthcare

July 1, 2021 - May 31, 2023

Developed predictive models for member risk stratification, hospital readmission, and chronic disease management using Scikit-learn, XGBoost, and PySpark. Designed and automated claims fraud, waste, and abuse detection models to reduce false claims. Built care gap identification pipelines by integrating structured claims, EMR, and pharmacy data to support value-based care initiatives. Implemented NLP pipelines on unstructured provider notes and call center transcripts for sentiment analysis and topic modeling. Created ETL workflows in Databricks and PySpark to process large-scale claims data with strong data quality validation. Partnered with clinicians to translate models into actionable insights, improving population health outcomes. Delivered interactive Power BI dashboards visualizing risk scores, anomalies, and quality metrics (HEDIS/STAR). Deployed ML pipelines on AWS with Docker/Kubernetes, and implemented HIPAA-compliant PHI security measures. Contributed to Snowflake OLAP data

AI/ML Engineer at PNC Bank

November 1, 2019 - June 30, 2021

Participated in agile ceremonies and delivered AI/ML solutions for financial services. Developed React components consuming Python APIs to display AI insights in real time. Performed univariate and multivariate analyses to detect data trends; cleaned and prepared datasets in Python and R. Built Power BI dashboards tracking KPIs like keyword trends and user engagement. Designed data quality workflows and conducted statistical evaluations to extract business insights. Constructed end-to-end data pipelines using Snowflake and AWS (S3, RDS). Addressed data gaps with imputation and robust preprocessing. Implemented fraud detection and segmentation models on imbalanced datasets using scikit-learn (e.g., Logistic Regression, Decision Trees, Random Forest, Gradient Boosting) and performed hyperparameter tuning and cross-validation. Executed Spark-based predictive modeling with Hadoop ecosystem for scalable ML tasks and delivered ad-hoc reporting and profiling insights. Implemented back-end val

AI Engineer at Western Digital

July 1, 2018 - October 31, 2019

Performed data analysis, migration, and preparation for customer segmentation and profiling. Implemented investigative calculations in Python (Pandas, NumPy, Seaborn, SciPy, Matplotlib) and conducted ETL/data warehousing procedures to build scalable pipelines for data extraction and transformation. Designed scalable algorithms for data mining and predictive modeling using statistical techniques. Used ETL tools to template and rapidly deploy pipelines; optimized ETL processes to Snowflake. Created data visualizations with Tableau and Excel, and contributed to GIT-based version control. Engaged in ER/Studio modeling for OLAP/OLTP contexts, and worked with Hadoop/Spark for predictive analytics.

Data Analyst at Lowe's Companies, Inc.

April 1, 2015 - June 30, 2018

Designed and implemented ML models for forecasting, customer segmentation, and recommendation systems to support retail analytics. Built scalable data pipelines using PySpark, Kafka, and Hadoop for ingestion, transformation, and model training on large datasets. Deployed AI/ML solutions into production with Docker, AWS EMR, and Lambda, with automated monitoring and scaling. Applied time-series forecasting techniques (ARIMA, Prophet, SARIMA) to improve demand planning and inventory management. Created end-to-end ETL workflows integrating Spark SQL, Sqoop, and Hive for real-time and batch analytics. Collaborated with stakeholders to align AI/ML solutions with retail strategy and built interactive dashboards in Tableau for model outputs and KPIs.