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krishnamami/README.md

Hi there , I’m Krishna Goud

🚀 Data & MLOps Leader @ Rocket LA (part of Rocket Companies)

$4B+ Business Growth | 📈 $800M+ Revenue Impact | Architecting AI-Driven, Cloud-Native Platforms for Scalable Growth

I’m a Data & AI Leader with deep expertise in building intelligent, scalable platforms that deliver measurable business impact. At Rocket LA, I lead the Data Engineering and MLops function — driving billions in originations and marketing optimizations by architecting real-time ML pipelines, modern cloud infrastructure, and enterprise AI strategy.

I am also contributing to the development of MeridioAI,a conversational AI startup focused on redefining customer engagement in the restaurant industry through smart, chatbot-driven experiences.

🔧 Featured Projects

Project Description
Fine_Tuning_LLM QLoRA-based LLM fine-tuning pipeline for enterprise GenAI use
Multi_Agent_Anamoly_Detection AI agents for intelligent anomaly detection in ML Ops systems
End to End MLOps pipelines with CI/CD End to End MLOps pipelines using CI/CD
Distributed_ML_Sagemaker_Pipelines Scalable ML pipeline on SageMaker for distributed training and deployment
MLOps with CI/CD using GitOps on AWS ECR End to End MLOps pipelines using CI/CD with GitOps and AWS ECR
AI Powered Taxanomy Generation Engine Agent based approach to generate Taxanomy with Pydantic Validation

🛠️ Technical Skills

  • Languages: Python, SQL
  • Frameworks: TensorFlow, PyTorch, Scikit-learn
  • Tools: AWS, SageMaker, Airflow, Docker
  • Databases: Snowflake,Databricks,Teradata,Oracle
  • Others: Git, CI/CD, Agile Methodologies,Kafka,Spark

🌐 Connect with Me

Pinned Loading

  1. MLOPS_end_end_CICD_Pipelines_Jenkins_Google_Cloud MLOPS_end_end_CICD_Pipelines_Jenkins_Google_Cloud Public

    A complete MLOps pipeline —featuring automated data ingestion, preprocessing, model training, and deployment using Jenkins-based CI/CD on Google Cloud Platform.

    Python

  2. Distributed_ML_Sagemaker_Pipelines Distributed_ML_Sagemaker_Pipelines Public

    Scalable SageMaker pipeline reducing model training time by 40% for enterprise ML.

    Python 1

  3. AI-Powered_Email_Campaign_Taxonomy-_Engine AI-Powered_Email_Campaign_Taxonomy-_Engine Public

    Automate extraction of taxonomy attributes from email campaigns using OpenAI's language models, FAISS for rule retrieval, and LangChain for orchestrating the logic.

    Python

  4. Multi_Agent_Anamoly_Detection Multi_Agent_Anamoly_Detection Public

    AI agent-based monitoring for real-time anomaly detection, intelligent alerting in large-scale data pipelines.

    Python

  5. MLOps-CICD_GitOps_AWS MLOps-CICD_GitOps_AWS Public

    A production-grade MLOps pipeline that automates the entire machine learning lifecycle — from data ingestion and preprocessing to model training and deployment — using CI/CD, GitOps, AWS ECR, EC2, …

    Jupyter Notebook