Aitor Ruano
Strategic Data Engineer
Barcelona, Catalonia, Spain
Summary
👤
Senior🎓
Top SchoolAitor Ruano is a Strategic Data Engineer based in Barcelona with 10 years of experience building scalable, high-availability systems at the intersection of data and AI. He combines hands-on expertise in Python and C/C++ with production MLOps and AI leadership roles across Google, SITA, Midokura and earlier work on autonomous driving systems. His background spans backend infrastructure (Kubernetes, Docker Swarm), safety-critical vehicle prototyping, and shipping ML pipelines into production, reflecting both deep technical craft and operational rigor. An active open-source contributor, he improved reward logic and lane-marking detection in a vision-based self-driving GTAV research plugin, showing a practical focus on simulation and perception. Collected academic training in telecommunications engineering and an MS in mathematics and computer science underpin his systematic approach to computation at scale. He is known for bridging research, product and security concerns to deliver robust, production-ready AI solutions.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Engineering - BE Telecommunications Engineering, Bachelor of Engineering - BE Telecommunications Engineering at UPC - ETSETB TelecomBCNMaster of Science - MS Mathematics and Computer Science, Master of Science - MS Mathematics and Computer Science at Universitat Rovira i Virgili
English, Catalan, Spanish, Japanese
Github Skills (8)
algorithm10
data-structures10
algorithms10
c-language10
game-development10
cprogramming-language10
data-structure10
pathfinding9
Programming languages (2)
Github contributions (5)
aitorzip/DeepGTAV
Sep 2016 - Nov 2017
A plugin for GTAV that transforms it into a vision-based self-driving car research environment.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:122 commits, 6 PRs, 122 pushes in 1 year 1 month
Contributions summary:Aitor primarily focused on modifying the reward logic and functionality within the GTAV plugin. Their work involved changes to the `rewards.cpp` file, including the implementation of a global reward function and improvements to lane marking detection. They addressed a bug related to equal distances in the center of the lane by modifying the distance map. These changes suggest an active role in refining the core gameplay mechanics of the self-driving car research environment.
pytorchvisiondeep-learninggtavcomputer-vision
aitorzip/Keras-ICNet
Nov 2017 - Dec 2017
Contributions:23 commits, 21 pushes, 1 branch in 19 days
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