Harshit Singh

Harshit Singh

Machine Learning Engineer

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location of Harshit SinghUrbana, Illinois, United States

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  • Timeline

  • About me

    Masters in CS @ UIUC - Seeking Opportunities || ML/SDE @PBC || ML @TCS || ML @Paperplane

  • Education

    • La Martinere College

      2008 - 2017
      School
    • City Montessori School

      2017 - 2019
      High School 95%
    • University of Illinois Urbana-Champaign

      2023 - 2025
      Master's degree Computer Science

      CS 411 Database Systems CS 412 Data MiningCS 440 Artificial IntelligenceCS 435 Cloud NetworkingCS 467 Social VisualizationCS 598 ML and Data SystemsCS 568 User-Centered Machine LearningCS 598 Deep Generative Models

    • SRM University

      2019 - 2023
      Bachelor of Technology - BTech Computer Science 9.72
  • Experience

    • Paperplane

      Aug 2021 - Nov 2021
      Machine Learning Engineer

      • Fine-tuned a CART-based drug recommendation model with Bayesian optimization, improving accuracy by 15%.• Built a graph pipeline (Python, NetworkX) to map symptom-diagnosis-drug relationships, reducing manual analysis time by 20%.• Leveraged parallel processing with Scikit-Learn and JAX's vmap, boosting classification accuracy by 7% on 1M+ patient records.

    • Tata Consultancy Services

      Jun 2022 - Sept 2022
      Machine Learning Engineer

      • Benchmarked Random Forest and XGBoost models for trading signal classification, increasing prediction accuracy by 25%.• Developed an end-to-end ETL pipeline using Python, SQL, and AWS (EC2, S3, SageMaker) to process 1M+ daily data points• Optimized LSTM-based time series forecasting with bidirectional LSTMs and attention mechanisms, improving long-range pattern recognition and reducing latency by 15% through batch inference and selective pruning.

    • Palm Beach County

      May 2024 - Dec 2024
      Software Engineer

      • Developed scalable ML pipelines for a Retrieval-Augmented Generation (RAG) system, integrating ElasticSearch and Neural Seek toimprove chatbot response accuracy to 96% through better feature engineering and inferencing.• Optimized data workflows by implementing preprocessing pipelines (fine-tuning Granite 13B on IBM Watson) and multi-threadedingestion with Python and Selenium, reducing manual data handling by 80%.• Enhanced data and infrastructure performance by 30% for a platform serving 1.6M+ residents by optimizing SQL queries withB-Tree indexing and partitioning strategies, ensuring real-time data availability for continuous model training and RAG pipelines.• Automated operational workflows (snapshots, backups, and patch updates) using Python scripts and Oracle RMAN, reducing down time by 60% and enabling MLOps best practices for data ingestion and inferencing. Show less

  • Licenses & Certifications

  • Volunteer Experience

    • Vice Chair

      Issued by Sitara Foundation on Sept 2021
      Sitara FoundationAssociated with Harshit Singh