P

Prachi Gupta

About

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Dallas, Texas, United States

Timeline

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Résumé

Jobs verified_user 0% verified
  • Amazon
    Staff AI/ML Engineer
    Amazon
    Jan 2021 - Current (5 years 10 months)
    • Built end-to-end ML and LLM features from problem definition through data pipelines, modeling,
    evaluation, deployment, and monitoring, improving system performance by 40%.
    • Developed LLM applications using retrieval-augmented generation RAG, orchestration workflows,
    LangChain frameworks, and structured extraction pipelines for real-world use cases.
    • Converted unstructured text data including logs, customer interactions, and search queries into structured
    signals such as topics, entities, intent, sentiment, and classification outputs.
    • Designed and maintained scalable data pipelines for training, inference, evaluation, and analytics using
    Python, Databricks, Spark, and distributed processing frameworks
  • Datascan
    Senior AI ML Engineer
    Datascan
    May 2018 - Dec 2020 (2 years 8 months)
    • Developed machine learning models for predictive analytics, anomaly detection, and risk assessment
    using Python, Scikit-learn, XGBoost, and TensorFlow, improving prediction accuracy by 18%.
    • Built NLP pipelines using spaCy and NLTK for processing enterprise documents and structured data
    sources.
    • Designed scalable ETL and data processing pipelines using Apache Spark, Hadoop, and Airflow for large-
    scale data processing.
    • Implemented fraud detection and anomaly detection systems using statistical modeling and machine
    learning techniques, reducing risk exposure by 28%.
    • Deployed machine learning models on AWS including EC2, S3, RDS, and Lambda in scalable production
    environments.
    • Built
  • Datascan
    AI Full Stack Engineer
    Datascan
    Jan 2015 - Apr 2018 (3 years 4 months)
    • Developed full-stack applications using Python, JavaScript, React, Node.js, and REST APIs for enterprise
    data platforms.
    • Built data ingestion and ETL pipelines using Python, SQL, and Hadoop for structured and unstructured
    data processing.
    • Designed backend services and APIs using Node.js and Express.js for data-driven applications.
    • Integrated machine learning models using Scikit-learn into applications for predictive analytics and
    reporting.
    • Developed dashboards and reporting tools using Tableau and business intelligence platforms.
    • Worked with relational and NoSQL databases including PostgreSQL and MongoDB for scalable storage
    solutions.
    • Implemented automation scripts using shel
Education verified_user 0% verified
  • University of Texas at Austin
    Bachelors of Science | Computer Engineering
    University of Texas at Austin
    Jan 2010 - Dec 2014 (5 years)