About me

Machine Learning Engineer with over 6+ years of experience.

I enjoy designing end-to-end ML pipelines—from data ingestion and preprocessing to model training, deployment, and monitoring.

Beyond the technical side, I value clean architecture, collaboration, and continuous learning. I’m driven by the challenge of making machine learning systems not just accurate, but dependable and scalable.

Technology stack

  • Languages
  • OS & Terminal
  • Editor's Choice
  • Backend Development
  • Data Science & Machine Learning
  • Machine Learning
  • AI
  • Cloud & Deployment
  • Observability
  • Testing
  • Web Automation
  • IaC
  • Automation
  • Cloud
  • Version Control
  • Database
  • ETL
  • Workflow Orchestrator
  • Notetaking

Certifications

  • Udmey

    MLOps

    Mlops Course

Resume

Experience

  1. Capgemini

    2024 - present

    Senior MLOps Engineer - Designed and maintained end‑to‑end ML workflows using Azure ML Studio, ensuring seamless model training, validation, deployment, and monitoring.
    - Automated CI/CD pipelines for ML using Azure DevOps, improving deployment speed and reducing manual effort across projects
    - Implemented MLflow tracking, model registry, and versioning workflows to bring consistency to experiment tracking and model governance.
    - Architected and operated a Feast Feature Store for consistent feature versioning, lineage, and reusability across credit‑risk models
    - Worked with key ML libraries (scikit-learn, pandas, numpy, XGBoost, LightGBM) to support data scientists in building robust credit‑risk models.
    - Collaborated with data science teams to operationalize credit scoring and risk prediction models, ensuring compliance with regulatory requirements.

  2. Ojcommerce

    2023 - 2024

    Associate MLOps Engineer - Designed and implemented end-to-end automated data pipelines to crawl, ingest, and transform buy-box data from the Amazon Marketplace in real-time. Incorporated robust fallback mechanisms to ensure continuity and reliability of data flow during service disruptions or API failures.
    - Built a system using Selenium to scrape real-time Amazon Buy-Box prices and applied an XGBoost model to predict optimal bid prices for vendors. Developed and deployed a machine learning model using XGBoost to accurately predict optimal bid prices for vendors, significantly increasing their chances of winning the Amazon buy-box. The model leveraged historical pricing trends, competitor behavior, and product-specific attributes to make data-driven pricing recommendations. Included a robust fallback to SQL-based pricing logic to ensure continuous pricing.
    - Deployed and managed the entire pipeline using Apache Airflow, automating the end-to-end flow from data ingestion to pushing updates to Amazon SP-API, with retries and failure handling.
    - Designed system monitoring and observability tools to track performance, scraping success, and API updates-contributing to an 18% increase in revenue over the previous year through more competitive pricing.

    - Built a pipeline to process vendor-submitted furniture documents containing product images and descriptions, categorizing them into appropriate buckets and refining labels for detailed classification.
    - Developed connectors to automatically publish enriched product data to marketplaces like Amazon, Wayfair, and Home Depot, aligning with each platform's format and taxonomy requirements.
    - Reduced manual effort for the catalog team by automating classification and listing tasks, resulting in faster product onboarding and improved SLA adherence across the catalog operations.
    - Trained CNN Model on DDP strategy on AWS Sagemaker and exports onnx format and served using AWS lambda service

  3. Math company, Bengaluru

    2022 - 2023

    Data Scientist - Performed statistical analysis to explore relationships between customer call durations and associated market sentiment
    - Contributed to media mix modeling efforts to evaluate the effectiveness of marketing channels. Conducted multi-touch attribution analysis to identify the contribution of each channel in the customer journey, optimizing marketing spend and ROI.
    - feeding into interactive Tableau dashboards to deliver actionable business insights
    - Conducted statistical analysis to examine customer call durations and market sentiment, while contributing to media mix modeling and multi-touch attribution to optimize marketing spend.
    - Delivered actionable business insights through interactive Tableau dashboards for improved decision-making.

  4. Tata Consultancy Services, Bengaluru

    2020 - 2022

    Database Administrator, IBM DB2 - Managed and maintained database performance. Performed regular backups, indexing, query optimization, and health checks to ensure smooth operation of data services.
    - Developed scripts to parse and collect metadata and execution status from scheduling systems or workflow tools.
    - Designed and implemented a system with collected SQL Server utilization metrics per job, job runtime, success/failure status, resource consumption, firewall or permission-related issues, and execution time. segmented by team ownership.
    - Built a structured data pipeline to aggregate, normalize, and store job-level insights, enabling historical trend analysis and operational diagnostics

Education

  1. The School of AI

    2023 — 2024

    Extensive Machine Learning Operations V5

  2. Scaler Academy Courses

    2021 — 2022

    Data Scientist & ML Operations

  3. Sona College of Technology

    2016 — 2020

    EEE

  4. Higher Secondary

    2014 — 2016

    NHSS

  5. High School

    2014-2016

    NHSS

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