MACHINE LEARNING DATA ENGINEERING

I'm an AI Engineer and Machine Learning Solutions Architect with 7+ years architecting, building, and deploying production-grade AI systems, driving measurable business transformation. I specialize in turning complex data challenges into intelligent solutions, reducing costs, improving efficiency, and creating competitive advantages.

What I Do:
I help organizations unlock artificial intelligence's full potential by designing end-to-end solutions addressing your business challenges. Unlike single-domain specialists, I architect complete solutions spanning data engineering, machine learning, MLOps, and cloud infrastructure—ensuring seamless integration and sustainability.

My Core Expertise:

Agentic AI & Autonomous Systems — I design intelligent agents automating complex workflows, reducing manual intervention by 70%, enabling autonomous decision-making at scale. Multi-agent systems with reasoning engines, memory management, and tool integration to solve real-world problems with 92%+ accuracy.

Generative AI & Large Language Models — I architect and deploy generative AI solutions, including RAG pipelines, fine-tuned models, and prompt optimization. Systems handle 500K+ daily queries with improved accuracy, reduced hallucination, and 28% lower operational costs.

Production Machine Learning — I've deployed 15+ ML models across computer vision, NLP, forecasting, and predictive analytics, serving 2M+ monthly predictions with 98.5% uptime. Specializing in feature engineering, model optimization, and measurable accuracy improvements (22%+ on critical metrics).

MLOps & Production Infrastructure — I architect robust MLOps ecosystems with automated CI/CD pipelines, achieving 99.7% deployment reliability and 99.9% SLA compliance. Includes model monitoring, drift detection, experiment tracking, and A/B testing frameworks.

Enterprise Data Engineering — I design scalable data infrastructure on AWS, Azure, GCP, processing 500GB+ daily. I optimize data warehousing, implement quality frameworks ensuring 98% reliability, and create data lakes, accelerating time-to-insight 60%.

Cloud Architecture & DevOps — I architect containerized, highly available applications using Docker, Kubernetes, and Infrastructure-as-Code. I design disaster recovery, implement auto-scaling, optimize costs—delivering 28% infrastructure savings.

Technical Leadership — Managed 100+ data scientists, trained 400+ professionals (90% job placement), mentored engineers with 100% promotion rates.
Why Organizations Choose Me:

End-to-End Solutions — Data to deployed models to MLOps. Complete solutions without referrals.
Proven Results — 15+ production models, 2M+ predictions monthly, 98.5% uptime, $250K+ savings, 45% efficiency gains.
Enterprise Quality — Production-ready, scalable, maintainable systems. Real business-critical solutions.
Business-Focused — Measurable outcomes: cost reduction, efficiency, revenue impact.

Work Terms

How I Work:

Strategic Consulting | Solution Architecture | Implementation & Deployment | MLOps Infrastructure | Team Augmentation | Custom Training

Engagement: Full-time (3-6+ months) | Part-time advisory (5-15 hrs/week) | Team augmentation | Training

Technical Skills:

AI/ML: Agentic AI | Generative AI | Deep Learning | NLP | Computer Vision | Forecasting | Feature Engineering

MLOps: CI/CD | Model Monitoring | MLflow | Docker | Kubernetes | Infrastructure-as-Code

Cloud: AWS (S3, Redshift, Glue, EMR, SageMaker) | Azure | GCP

Data: Apache Spark | Databricks | Data Warehousing | ETL/ELT | Kafka | Airflow | SQL

Frameworks: TensorFlow | PyTorch | Scikit-learn | XGBoost | Pandas | LangChain | Hugging Face

Languages: Python (Expert) | SQL (Expert) | Scala, Java