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Prithiv Rajkumar

@prithivrajkumar

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Machine Learning Engineer specializing in end-to-end pipelines, predictive models, and MLOps.

India

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What I'm looking for

I am seeking roles where I can build and deploy scalable ML systems, collaborate in cross-functional teams, drive measurable business impact, and grow in MLOps and production ML engineering.

I am a Machine Learning Engineer with hands-on experience building end-to-end data pipelines, deploying ML systems, and delivering predictive models across healthcare, consulting, and financial forecasting domains.

My work emphasizes scalable, production-ready solutions: I have architected fault-tolerant RAG systems on AWS, dockerized and deployed pipelines to serverless infrastructure, and integrated monitoring and CI/CD for reliable model rollout.

I improved heart failure prediction AUC-ROC from 0.6 to 0.8 through model experimentation and Bayesian optimization, automated data orchestration with Airflow and MLflow, and implemented drift detection to maintain model performance in production.

I combine strong software-engineering practices with data science — building feature engineering pipelines on Spark, optimizing SQL and Snowflake queries, and creating interpretable models and dashboards to convert complex data into actionable business insights.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Engineer

Current

SquarkAI

Aug 2025 - Present (5 months)

Architected a fault-tolerant RAG system on AWS integrating Bedrock and FAISS with Anthropic fallback, Dockerized and deployed inference pipelines on AWS Lambda, and improved retrieval speed by 20% through vector DB optimizations.

RAG Lambda Faiss Docker fastAPI Vector Databases MLOps

Data Scientist Intern

Johnson and Johnson Medtech

Jul 2024 - Dec 2024 (5 months)

Automated heart time-series preprocessing and orchestration with Airflow and MLflow, raised heart failure prediction AUC-ROC from 0.6 to 0.8 via XGBoost/LSTM and Bayesian optimization, and integrated drift monitoring with Alibi Detect.

Apache Airflow MLFlow XGBoost Bayesian Optimization SHAP Alibi Detect

Data Analyst

ZoomRx Healthcare Consulting

Jul 2021 - Dec 2022 (1 year 5 months)

Analyzed large client datasets to surface patient behavior metrics via Pandas/SciPy and Tableau, optimized Snowflake SQL reducing query time by 30%, and deployed SARIMAX forecasting that produced a 12% lift in weekly prescriptions.

Python Pandas Scipy SQL Snowflake Tableau A B Testing

Software Engineer

KPIT Technologies

Nov 2019 - Jul 2021 (1 year 8 months)

Built scalable feature-engineering pipelines on real-time automotive telemetry with Spark and Cassandra, productionized ML microservices with Docker/Kubernetes and CI/CD, and implemented monitoring and testing achieving 95% code coverage.