Khushbu Kakdiya
Ai Ml Engineer @CVS Health
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WORK HISTORY
Ai Ml Engineer @CVS Health
US
Led development of production ML and GenAI workflows supporting enterprise healthcare automation, improving operational accuracy and reducing manual processing effort across clinical use cases.• Designed and deployed RAG-based AI services for document understanding and information retrieval, enabling faster access to policy and clinical knowledge from unstructured data sources.• Built end-to-end ML pipelines covering data ingestion, feature engineering, model training, deployment, and monitoring, reducing model release cycles and improving delivery reliability.• Developed scalable API-based inference services using FastAPI and cloud infrastructure, supporting low-latency real-time predictions for downstream applications.• Implemented model monitoring, drift detection, and performance tracking, improving production model stability and enabling proactive issue identification.• Collaborated with data engineering, product, and compliance teams to translate business requirements into deployable, compliant AI solutions.
EDUCATION
Cleveland State University
Master's degree, Computer Science
Gujarat Technological University (GTU)
Bachelor of Engineering
Cleveland State University
Master of Computer Science
Hasmukh Goswami College Of Engineering
Bachelor of Engineering, Computer Engineering
ABOUT KHUSHBU KAKDIYA
Artificial Intelligence Machine Learning Engineer with 5+ years of hands-on experience across the full AI lifecycle, including data analysis, feature engineering, machine learning modeling, scalable data pipelines, and production deployment of ML and GenAI systems. Proven background in building end-to-end ML solutions using Python, SQL, and distributed data processing frameworks, with recent focus on GenAI, RAG pipelines, and cloud-native AI services. Experienced in deploying models via APIs, implementing MLOps practices, and monitoring model performance in production environments. Demonstrated career growth from core data science and data engineering roles to owning applied AI solutions aligned with enterprise and business requirements.
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