Ricardo García Ramírez

I'm a Senior Software Engineer with 7+ years of experience building data systems, ML pipelines, automation tooling, and backend services across enterprise and scientific environments. M.Sc. in Data Science from Pontificia Universidad Católica de Chile (Distinction) — thesis on probabilistic reconstruction of cardiac networks from ECG signals using Bayesian inference and computational modeling. Biomedical Engineering background from Tec de Monterrey. Currently at MSCI designing analytics and monitoring tools for large-scale financial data systems.

My technical depth sits at the intersection of data engineering, machine learning, and practical software delivery. I've built reproducible ML pipelines using JAX and scikit-learn for real research problems, designed ETL workflows that go from raw file formats to queryable analytics assets, and implemented RAG systems from the vector chunking layer (Rust/PyO3) all the way through to retrieval and LLM orchestration. I take Bayesian approaches seriously — the thesis work on Gaussian processes and probabilistic inference wasn't academic detour, it informs how I think about uncertainty in ML systems today.

My freelance work focuses on Python tools with clear scope and real handoff: automation pipelines, data extraction workflows, RAG/LLM applications, dashboards, and scientific Python packages. If you have defined inputs, expected outputs, and a deadline — I can work with that.

I taught bioinstrumentation at Tec de Monterrey, have 5 peer-reviewed publications in biosensing and BioMEMS, and write about software engineering and Python on Medium. The research background isn't decoration — it's why the scientific Python work (PurkinjeUV, JAX-BO) exists, and why I default to reproducible, documented, tested code over notebooks.