Hi, I'm |
Senior ML Platform Engineer & AI Systems Architect
I design and build scalable machine learning platforms that power intelligent applications at enterprise scale. With years of experience across the entire ML lifecycle, I transform data science prototypes into production-ready ML systems.
About Me
I'm a passionate ML Platform Engineer specializing in designing end-to-end ML platforms that seamlessly integrate data pipelines, model training, deployment, and monitoring systems. My expertise spans enterprise-scale machine learning infrastructure and cloud-native architectures.
From edge computing optimizations to multi-cloud MLOps pipelines, I've worked on every stage of the ML lifecycle. I believe in building robust, secure, and scalable systems that enable data scientists to focus on innovation while ensuring models perform reliably in production.
100+
ML Models Deployed
99.9%
Platform Uptime
50+
TB Data Processed
Professional Experience
6+ years of building scalable ML systems and platforms
Senior ML Platform Engineer
Leading the design and implementation of enterprise-scale ML platforms serving 50+ data scientists. Built automated model training, deployment, and monitoring systems achieving 99.9% uptime.
Key Achievements
- Designed and deployed ML platform handling 1000+ models in production
- Reduced model deployment time by 75% through automated CI/CD pipelines
- Implemented real-time monitoring system reducing model drift detection time by 90%
- Led team of 8 engineers across ML infrastructure and DevOps
Technologies Used
ML Platform Engineer
Developed and maintained ML infrastructure for real-time recommendation systems and fraud detection models. Focused on scalability, performance optimization, and system reliability.
Key Achievements
- Built real-time recommendation engine handling 1M+ requests per minute
- Implemented fraud detection system processing 10M+ daily transactions
- Optimized model serving infrastructure reducing latency by 60%
- Established MLOps best practices and monitoring standards
Technologies Used
ML Engineer
Worked on end-to-end ML projects from data preprocessing to model deployment. Collaborated with cross-functional teams to deliver AI-powered solutions for various business domains.
Key Achievements
- Developed computer vision models for automated quality inspection
- Built NLP pipeline for customer sentiment analysis
- Created edge AI framework reducing model size by 90%
- Implemented A/B testing framework for ML model evaluation
Technologies Used
6+ years
Total Experience
3
Companies Worked
50+
Team Members Led
Skills & Technologies
ML Frameworks & Tools
Cloud & Infrastructure
Data & MLOps
Programming & Databases
Featured Projects
Enterprise ML Platform
Built a comprehensive ML platform serving 50+ data scientists with automated model training, deployment, and monitoring capabilities.
Real-time Recommendation Engine
Designed and implemented a high-performance recommendation system handling 1M+ requests per minute with sub-100ms latency.
Multi-Cloud MLOps Pipeline
Created a vendor-agnostic MLOps pipeline supporting AWS, GCP, and Azure with automated CI/CD for ML models.
Edge AI Optimization Framework
Developed framework for deploying ML models on edge devices with 90% size reduction while maintaining accuracy.
Fraud Detection System
Built real-time fraud detection system processing 10M+ transactions daily with advanced ML algorithms.
Data Quality Monitoring
Implemented comprehensive data quality monitoring system with automated alerting and drift detection.
Get In Touch
I'm always interested in discussing new opportunities, innovative ML projects, or collaborating on cutting-edge technology solutions. Let's connect!