Technical Stack & MLOps Workflow

I leverage a multidisciplinary stack to bridge the gap between high-level project coordination and deep technical implementation in AI and Earth Sciences.

AI & Data Engineering (The AI Factory Focus)

• MLOps & Scaling: Architecting end-to-end pipelines for AI surrogates using PyTorch, focusing on model deployment and monitoring on the MN5 AI partition.
• Data Workflows: Expert-level manipulation of terabyte-scale datasets using Xarray, Dask, and NetCDF, ensuring high-throughput data availability for AI training.
• AI Integration: Strategic alignment of AI services with traditional Earth System Models (EC-Earth, NEMO) to accelerate physical simulations.

HPC Orchestration & Project Management

• Workflow Coordination: Lead developer of Autosubmit templates, managing reproducible, multi-institution research workflows on Tier-0 systems.
• System Administration & Optimization: Expert in Slurm job scheduling, software environment management (LMOD/Conda), and optimizing hardware utilization for GPU-heavy AI workloads.
• Agile Coordination: Driving technical excellence within international consortia using Agile and Scrum methodologies for software development lifecycles.

Mathematical Foundations & Performance

• Numerical Excellence: Strong foundations in Applied Mathematics, including finite difference methods and multiscale averaging (♾️ ∫).
• Performance Programming: Developing high-performance model components in Fortran, C++, and Python.

Focused on the technical coordination and engineering infrastructure required to realize the next generation of AI-enhanced Climate Science.