Luis G. Chinchilla-Garcia

I am

About Me

I am a Machine Learning Engineer who also delves into the worlds of Data Engineering and Web Development. Currently, I am a Data Engineer at Red Bull, where I focus on creating scalable end-to-end machine learning models for Recommender Systems.

I graduated from the University of California, Los Angeles with a BS in Astrophysics. During that time, I completed four years of research as part of a research fellowship and was also a co author in a paper (details below).

Skills and Experience

For Machine Learning Engineering, some of my responsibilities have included:

  • Actively researching and prototyping machine learning models to personalize product recommendations

  • Deploying machine learning models on cloud services as part of an end-to- end machine learning workflow

  • Developing & maintaining end-to-end machine learning pipelines that are scalable and cost effective



Tensorflow Probability




Experience Timeline

Study of Filaments Near the Galactic Center

Astrophysics Research: UCLA


Conducted image processing and statistical analysis on data take by space telescopes WISE and SPITZER on gas filaments AFGL-5376 and Double Helix Nebula in the Galactic Center.

Radio Transient Classification

Astrophysics Research: UC Berkeley

(Summer 2016)

Used clustering techniques to classify fast radio transients. This work was done under the mentorship of Dr. Casey Law and Dr. Carl Heiles.

Search for Technosignature in TRAPPIST-1

Astrophysics Research: UCLA


Collected over three terabytes of observational data from the 100m Green Bank telescope to identify possible technosignatures near TRAPPIST-1.

Lead Machine Learning Engineer



Leading the data science team toward researching, developing & experimenting machine learning models to solve problems in Natural Language Processing, personalized UI/UX, and business-oriented analysis.

Data Engineer

Red Bull


Research, prototype, and deploy machine learning models on cloud services to personalize product recommendations as part of an end-to-end machine learning workflow.

Contact Me

I'm always open for discussions, so feel free to contact me!