Available to hire
Hi, I’m Suma Kake, a Machine Learning Engineer focused on Generative AI, NLP, and scalable ML microservices. I design and deploy production‑grade AI systems and enjoy turning complex problems into practical, business‑driving solutions.
In cross‑functional teams, I combine Python, FastAPI, LangChain, and cloud platforms like AWS to deliver reliable, scalable AI applications that improve model performance and automate workflows in fast‑paced, Agile environments.
Skills
Language
English
Fluent
Work Experience
Artificial Intelligence/Machine Learning Engineer (Generative AI S) at Vitharka Inc.
January 1, 2024 - PresentDesigned and developed a Generative AI‑based web application integrating LangChain, LangGraph, OpenAI models, and MongoDB Vector Store for real‑time document retrieval and context‑aware chatbot responses. Architected RAG‑based pipelines enabling hybrid retrieval of structured and unstructured content, improving chatbot accuracy and contextual relevance. Implemented contextual retrieval with prompt augmentation and vector similarity. Introduced vector filtering to apply search filters (tags or source types) for targeted responses. Built Python FastAPI microservices to generate embeddings, perform similarity search, manage knowledge bases, and query vector stores. Developed secure, scalable Java Spring Boot services for user registration, JWT authentication, chat history management, and integration with AI services. Created a modular ReactJS frontend for user interaction, document upload, and chatbot communication. Implemented real‑time monitoring, logging, and alerting across
Data Scientist at IQVIA
September 1, 2020 - December 1, 2022Bronze Awardee – IQVIA Impact Program. Designed and evaluated logistic regression and deep learning models (TensorFlow) to predict healthcare provider engagement and campaign responsiveness. Performed feature engineering, data preprocessing, and outlier analysis to improve accuracy. Applied A/B testing and model validation to compare personalized campaigns. Conducted time‑based cohort analyses to track engagement across providers over multiple campaigns. Automated ETL pipelines using Python and SQL to process multi‑channel campaign data. Created Tableau dashboards connected to Amazon Redshift to monitor campaign performance. Reduced manual data processing by 95% through automation and SQL optimization. Achieved 75% success rate in campaign targeting by refining predictive models. Built scalable ReactJS dashboards and full‑stack applications with protected routes and role‑based access controls. Contributed to frontend unit testing with Jest and React Testing Library.
Education
Master of Science in Artificial Intelligence and Business Analytics at The University of Texas at Dallas
January 1, 2023 - December 1, 2024Bachelor of Science at National Institute of Technology, Nagpur, India
August 1, 2016 - May 1, 2020Qualifications
Azure AI Fundamentals Certified
January 11, 2030 - December 24, 2025Dean’s Excellence Scholarship
January 11, 2030 - December 24, 2025Industry Experience
Software & Internet, Healthcare, Manufacturing, Professional Services
Skills
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