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  • Cluster Innovation Centre, University of Delhi
  • Delhi
  • 16:31 (UTC +05:30)
  • LinkedIn in/abhik-rai

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Achievement: Pull Shark

Achievements

Achievement: Pull Shark

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Abhishek-Kumar-Rai5/README.md

Hi, I'm Abhishek Kumar Rai

Backend and Data Systems Developer focused on building reliable data pipelines, scalable backend services, and reproducible deployment workflows.

I design production-ready systems involving structured data ingestion, API services, containerized infrastructure, and automated deployment pipelines.

Core Engineering Focus

  • Data ingestion and validation pipelines
  • Backend API and service development
  • Containerized deployment and infrastructure automation
  • CI/CD and system reliability
  • Debugging and stabilizing production systems

Current Direction

  • Modernizing legacy data platforms
  • Designing structured data ingestion workflows
  • Improving deployment reliability and automation
  • Contributing to open-source system and infrastructure projects

Technical Stack

Languages Python | SQL | JavaScript

Backend FastAPI | Flask | REST APIs

Infrastructure Docker | CI/CD | Linux

Data & Systems ETL Workflows | File Processing | Logging | Monitoring

Key Projects

ML Deployment Framework

Containerized backend service for model deployment and inference.

Key capabilities:

  • FastAPI-based service architecture
  • Dockerized deployment
  • API-driven prediction workflow
  • Reproducible environment setup

Secured CI/CD Pipelines

Automated CI/CD workflow for testing, validation, and deployment.

Key capabilities:

  • Continuous integration and deployment
  • Automated testing pipeline
  • Security and validation checks
  • Deployment automation

Email Classification Pipeline

Structured data processing pipeline for text classification.

Key capabilities:

  • Data ingestion and preprocessing
  • Modular pipeline design
  • Training and evaluation workflow
  • Reproducible processing system

MLOps Car Price Pipeline

End-to-end machine learning pipeline with real-time prediction service.

Key capabilities:

  • API-based prediction service
  • Workflow orchestration
  • Monitoring and logging
  • Deployment-ready architecture

Engineering Principles

  • Build systems that are deployable and maintainable
  • Design workflows that are reproducible
  • Prioritize reliability over complexity
  • Keep system components modular and testable

Currently Working On

  • Improving deployment reliability in backend systems
  • Strengthening data ingestion and validation workflows
  • Contributing to open-source system modernization

Contact

Email: rai.abhishek5140@gmail.com

GitHub: https://github.com/Abhishek-Kumar-Rai5

Popular repositories Loading

  1. Matlab-Fused-Flipbook-Animation Matlab-Fused-Flipbook-Animation Public

    Computational graphics project in MATLAB demonstrating mathematical modeling of frame-by-frame motion (flipbook simulation).

    MATLAB

  2. Email-classification-pipeline Email-classification-pipeline Public

    Modular NLP pipeline for spam detection and sentiment classification using TF-IDF features and classical ML models.

    Jupyter Notebook

  3. ML-deployment-framework ML-deployment-framework Public

    Modular ML deployment framework integrating FastAPI backend with Streamlit frontend for model serving.

    Python

  4. Secured-CI-CD-Pipelines Secured-CI-CD-Pipelines Public

    DevSecOps-based CI/CD pipeline integrating security scanning, automated testing, and secure deployment workflows.

    TypeScript

  5. Mlops-car-price-pipeline Mlops-car-price-pipeline Public

    End-to-end MLOps pipeline for car price prediction with training, monitoring, and FastAPI-based real-time serving.

    Python

  6. dataloom dataloom Public

    Forked from c2siorg/dataloom

    Project is to design and implement a web-based GUI for data wrangling, aimed at simplifying the process of managing and transforming tabular datasets. This application will serve as a graphical int…

    JavaScript