Miguel Alonso
Senior Member Of The Technical Staff at Gambit AI
Miami, Florida, United States
Summary
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Rockstar🎓
Top SchoolMiguel Alonso is a Senior Member of the Technical Staff with 20+ years blending machine learning, AI, and software engineering to deliver production-grade systems in computer vision, robotics, AR, energy, and autonomous systems. He bridges research and product delivery—leading teams of 5–30 through requirements, design, and CI/CD-driven implementation while remaining hands-on in Python, C/C++, C#, and Java. His recent work spans building full-body teleoperation pipelines, simulation-driven sim-to-real transfer for humanoids, and LLM-driven NPC tooling at Unity, where he also maintained the widely used Unity ML-Agents open-source toolkit. An academic entrepreneur as a former associate professor and center director, he has repeatedly converted research into deployed products and grant-funded projects. Based in Miami, he combines deep reinforcement learning and optimal control expertise with a practical knack for documentation and tooling—evident from his contributions improving ML-Agents API docs and automation for reproducible docs generation.
11 years of coding experience
25 years of employment as a software developer
Ph. D. Electrical and Computer Engineering - Image Processing Computer Vision Intelligent Control, Ph. D. Electrical and Computer Engineering - Image Processing Computer Vision Intelligent Control at Florida International UniversityLean LaunchPad Educator Entrepreneurship/Entrepreneurial Studies, Lean LaunchPad Educator Entrepreneurship/Entrepreneurial Studies at National Collegiate Inventors and Innovators Alliance
Spanish, English
Stackoverflow
781reputation
34kreached
1answer
0questions
gdb
top-5%
debugging
top-5%
Github Skills (9)
markdown10
deep-reinforcement-learning10
markdown-it10
python10
documentation10
machine-learning9
debugging9
gdb9
clion6
Programming languages (4)
Github contributions (5)
Unity-Technologies/ml-agents
Mar 2021 - Jan 2023
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Role in this project:
Technical Writer & Documentation Specialist
Technical Writer & Documentation SpecialistContributions:5 releases, 94 reviews, 165 commits in 1 year 10 months
Contributions summary:Miguel primarily focused on updating and expanding the API documentation for the ML-Agents toolkit, including adding Python Low Level API documentation. They made edits to the documentation, fixed docstring issues, and implemented a pre-commit hook to automatically generate markdown documentation using `pydoc-markdown`. The user also updated the docs to set epsilon to be linear by default. They also added documentation for new features like the training area replicator.
servedeep-reinforcement-learningtrainingunityreinforcement
maj-personal-repos/UnDeepVO
Feb 2018 - Apr 2020
UnDeepVO - Implementation of Monocular Visual Odometry through Unsupervised Deep Learning
Contributions:17 commits in 2 years 2 months
visual-odometrydeep-learningodometryunsupervisedoptical-flow
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