MLOps Engineer | Building Scalable & Production-Ready AI Systems
About Me
- MLOps Engineer passionate about automating and scaling machine learning solutions.
- Data Scientist experienced in Machine Learning, Deep Learning, NLP, and Computer Vision.
- Skilled in Cloud Deployments (AWS EC2, S3, EKS, ECR) and CI/CD Automation (GitHub Actions).
- Focused on building production-grade, maintainable, and scalable AI systems.
Core Expertise
- End-to-End MLOps Pipelines
- Machine Learning and Deep Learning Solutions
- Natural Language Processing (NLP) and Computer Vision
- Experiment Tracking (MLflow), Model Versioning (DVC), Model Registry
- CI/CD Automation (GitHub Actions)
- Docker, Kubernetes (AWS EKS) Deployment
- AWS Cloud Services (EC2, EKS, S3, ECR, IAM)
- Monitoring and Observability (Prometheus, Grafana)
- Scalable ML Systems Architecture
Tech Stack & Tools
- Python | SQL | Bash | Linux
- MLflow | DVC | Airflow
- Docker | Kubernetes (AWS EKS)
- AWS (SageMaker, Lambda, CloudWatch, S3, EC2, ECR, IAM, EKS)
- Git | GitHub Actions | CI/CD Pipelines
- Prometheus | Grafana
Featured Projects
MLOps NLP Capstone Project
- Built a production-ready NLP MLOps pipeline for sentiment analysis.
- Integrated DVC for data versioning, MLflow for experiment tracking.
- Deployed as a Dockerized microservice on AWS EKS with CI/CD via GitHub Actions.
- Real-time monitoring and alerting with Prometheus and Grafana.
MLOps Vehicle Insurance Prediction Pipeline
- Developed an end-to-end MLOps solution to predict vehicle insurance responses.
- Achieved a 23.5% improvement in F1-score through model optimization.
- Deployed pipelines on AWS, utilizing Docker, CI/CD workflows, and MongoDB.
US Visa Approval Prediction (MLOps)
- Engineered a scalable machine learning pipeline for visa approval prediction.
- Achieved 95% model accuracy, deployed with Dockerized CI/CD workflows.
- Data storage and retrieval managed via MongoDB.
Food Delivery Time Prediction ML Pipeline
- Designed a modular ML pipeline to predict food delivery times.
- Implemented advanced regression models including XGBoost and Random Forest.
- Ensured robust data validation, logging, and custom exception handling.
Let's Connect
I'm open to collaborations, freelance opportunities, or full-time roles in MLOps & AI Engineering.
Feel free to connect or drop a message!:
Email: 420kumarahul@gmail.com
Building in public. Learning every day. Let's connect!