ML Engineer & Software Architect
🔠I specialize in building robust machine learning and software utilities and services.
🌱 I create high-quality libraries and tools that prioritize reliability, performance, and usability.
Experience:
• PyTorch Algorithm Development: Optimizing CUDA operations for data processing and model operations (training/prediction) locally and in cloud environments
• MLOps Orchestration: Managing ML operations with and without CUDA in cloud for training, evaluation, and deployment
• Cloud ML Architecture: Designing reliable, highly available ML services with agility for change and updates
• Research Automation: Automating research and experimentation of machine learning in cloud environments
• LLM & Agent Technology: Deploying LLMs to GCP and Kubernetes, creating backend engineering servers for LLM streaming and MCP tool servers
My Projects
Here's a collection of my open-source projects:
activations-plus
A Python package providing a collection of activation functions not implemented in PyTorch.
tabnet
Deep learning architecture specifically for tabular data, combining interpretability and high predictive performance.
tab-right
Python package designed to simplify analysis of tabular data for inference models with powerful diagnostics and interpretability.
prob-spaces
Create probability distributions from Gymnasium spaces with a simple and intuitive interface for reinforcement learning environments.
pandas-pyarrow
Simplifies the conversion of pandas backends to pyarrow, allowing a seamless switch to pyarrow pandas backend.
ml-orchestrator
Define Kubeflow Pipeline (KFP) Components with Python Dataclasses for dataclass-driven component definition.
dev-kit-mcp-server
A Model Context Protocol (MCP) server for agent development tools, providing scoped authorized operations in projects.