About the Company
GE Vernova is a global leader in the wind energy sector, designing, manufacturing, and servicing wind turbines and hybrid energy systems across the world.
During my engagement, the focus was Wind Resource Assessment (WRA) engineering, where accurate wind speed, direction, and turbulence modeling are critical to site selection and turbine performance optimization.
My Journey There
I worked on the optimization of meteorological analysis scripts. By moving numerical calculations from standard Python loops to NumPy vectorized broadcasting, we accelerated key tasks by 5x to 10x.
I also led the type safety and code quality modernization, migrating the codebase to Python 3.1x using custom static analysis scripts to automatically insert type hints and enforce lint constraints with uv and ruff.
Concurrently, I resolved scaling observability gaps by architecting Grafana and Prometheus monitoring, making Kubernetes cluster node utilization fully visible to the operations team.
Key Deliverables & Architectures
- [01]Wind Resource Assessment (WRA) Engineering: Developed and maintained a proprietary Python ecosystem for complex meteorological analysis, utilizing NumPy for vectorized operations and broadcasting to process SODAR (Sonic Detection and Ranging) and meteorological mast data.
- [02]Mathematical Modeling: Implemented advanced time-series processing techniques, including detrending and temporal decomposition, to analyze air mass density stability and hub/mast positioning for wind turbine deployment.
- [03]Infrastructure Optimization: Refactored critical Airflow DAGs using vectorized algorithms, achieving a 5x to 10x acceleration in task execution and significantly increasing pipeline reliability.
- [04]LLM-Driven Migration: Spearheaded the migration of 4+ core services to Python 3.1x, developing custom LLM-based static analysis scripts to automate type-hinting, signature refactoring, and dependency resolution (UV/Ruff integration).
- [05]Observability: Architected a monitoring stack (Grafana, Loki, Prometheus), reducing incident resolution time by enabling real-time tracking of GPU-accelerated Kubernetes clusters.
Chronicles & Artifacts
WRA Wind Farm telemetry analytics dashboard built to monitor rotor RPM, pitch angles, and vectorized wind data.