I build AI and data products and platforms — from architecture to production
I design and ship complete systems — architecture, data, models, and product. Creator of Ciaren, a visual workflow builder for data and machine learning pipelines, and maintainer of open-source Python libraries used by data teams worldwide.
8+
Years building ML systems
19.4K+
Monthly PyPI downloads
467+
GitHub stars
ciaren — ml_pipeline.workflow
▶ Ciaren in action — real demo, no mockups
// Flagship Product
Ciaren
Visual workflows for data pipelines and lightweight ML
Build data pipelines on a visual canvas, preview every step on real data, and export clean Python. Local-first, open core, and extensible through a signed plugin system.
Drag-and-drop canvas with 80 built-in nodes
Real-time preview on your actual data
Exports clean Python — pandas or Polars
Runs locally — no proprietary runtime, no lock-in
Signed plugin system with 10 extension points
Plugin marketplace coming soon
ciaren — order_status_prediction.workflow
export → clean Python
Real product screenshots — no mockups
One ecosystem: products, open source, and the knowledge behind them
Products under active development, open-source libraries adopted by the community, and technical content that documents how everything is built.
Open source, proven by the community
Python libraries with years of maintenance, steady releases, and adoption you can verify: public code, documentation, and downloads.
Sklearn Genetic Opt
A scikit-learn-compatible library for hyperparameter tuning and feature selection powered by evolutionary algorithms. A drop-in replacement for GridSearchCV and RandomizedSearchCV — finds optimal parameters faster across any estimator, pipeline, or callable. Actively maintained since 2021, published on PyPI and conda-forge, and used in production ML pipelines by teams worldwide.
381 stars
4.2K+ downloads/mo
98 documentation pages
Pyworkforce
Pyworkforce
A Python library for workforce management optimization: Erlang-C queue modeling for call center staffing, LP-based shift scheduling, and multi-skill rostering. Built for operations teams that need rigorous mathematical solutions — not heuristics.
86 stars
15.3K+ downloads/mo
Iterixs
Iterixs
An interactive learning platform for Data Science and Machine Learning — notebooks and SQL that run entirely in the browser, a skill graph that shows exactly what to learn next, guided learning paths toward data roles, and spaced-repetition review. Currently in private development.
Open source impact
Live metrics from the libraries, documentation, and content I maintain.
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Python packages
0+
Monthly PyPI downloads
0+
GitHub stars
0+
Documentation pages
Guides, tutorials, examples & API reference
0+
Technical articles
0+
Years building ML systems
Technical Articles
Writing on AI, ML engineering, and open-source development
Explore by topic
Community
Where I share code, writing, and discussion with the ML and open-source community.
Who builds this
Hi, I'm Rodrigo
The person behind Ciaren, sklearn-genetic-opt, PyWorkforce, and Iterixs — designing and building products and platforms for AI and data, and shipping production ML systems.
Everything I build starts as a real problem from production systems — a hyperparameter search that never finishes, a scheduling nightmare, a pipeline nobody can maintain. Some solutions become open-source libraries; the bigger ones become products.
The rule across this site is the same one I work by: show the work. Code, releases, documentation, and running software over claims.
Architecture & product engineering
For companies building something substantial: AI platforms, data infrastructure, and complete products — from architecture decisions to production systems.
AI platforms
LLM, RAG, and agent systems designed for production — with evaluation, cost, and reliability solved.
Data infrastructure
Pipelines, streaming, and data platforms that scale — the foundation every AI system stands on.
ML systems & MLOps
Training, deployment, monitoring, and retraining loops that keep models useful after launch.
Platform architecture
Services, plugins, APIs, and the trade-offs that decide how far a product can go.
Applied optimization
AutoML, evolutionary algorithms, forecasting, and scheduling — the specialty behind my open-source libraries.
Developer tooling
Internal tools, documentation systems, and developer experience that multiply an engineering team.
Building an AI or data platform?
I design and build critical systems end to end — architecture, data, models, and product. If that’s the scale you’re working at, let’s talk.