What I Can Do
Hover over each panel to explore my core capabilities across ML, data, and engineering.
ML Pipelines & MLOps
Machine Learning
AI Platform Engineering
Build company-wide AI infrastructure — centralized MCP servers, LLM API gateways, and governance tooling — so every team can use AI safely against internal data with proper cost attribution.
- Centralized MCP Server (Streamable)
- LLM API Gateway on Bedrock
- Usage & Cost Tracking by Team / User
- RBAC, Audit Logs & Admin Controls
Machine Learning & MLOps
Design and deploy end-to-end ML pipelines — from raw data ingestion to production model serving. Experienced with MLflow, Airflow, and Kubernetes-based model deployment.
- Model Training & Evaluation
- MLflow Experiment Tracking
- Automated Retraining Pipelines
- Real-time Inference at Scale
Data Engineering
Build robust ETL pipelines that process terabytes of data reliably. Skilled in Apache Airflow orchestration, SQL/NoSQL databases, and time-series storage.
- Apache Airflow Orchestration
- Data Warehouse Design
- Time-Series with InfluxDB
- Redshift & PostgreSQL
Full Stack Development
Deliver complete web applications from backend API to polished frontend UI. Proficient in NextJS, React, Python FastAPI, and Docker-based deployments.
- NextJS / React Applications
- Python Backend APIs
- MySQL & REST Integration
- Responsive UI Design
DevOps & Infrastructure
Architect and manage containerised workloads with Kubernetes. Implement GitOps workflows, reverse proxies, and automated CI/CD pipelines.
- Kubernetes (k3s) Clusters
- Docker Compose & Helm
- FluxCD GitOps
- Traefik Reverse Proxy
Self-Hosted Systems
Design and maintain a production-grade homelab running monitoring, AI, and media services — all on-premise with SSO and persistent storage.
- Ollama / OpenWebUI (Local LLM)
- Grafana + InfluxDB Monitoring
- Pi-hole & Privoxy
- TrueNAS RAID-Z Storage