Alvaro Gaona is a research engineer with 10 years of experience combining signal processing, control theory and software engineering to build autonomous mobile vehicles and scalable ML services. He has led production deployments of ML inference (Triton, TensorRT, ONNX) and cost-optimizations for GPU workloads while also designing robust cloud-native systems for bioinformatics and telecom. His background spans hands-on robotics research in Buenos Aires, high-impact engineering at Roche and Telecom Argentina, and leadership as a Lead Software Engineer at ASAPP. Alvaro is equally comfortable compiling and tuning models for inference as he is architecting fault-tolerant CI/CD pipelines and migrating large databases. He prioritizes collaboration and mentorship—teaching computational thinking and supporting junior engineers—while contributing to open-source projects and pursuing motorsports in his free time. Based in Madrid and completing an MSc in Automation & Robotics, he brings a rare blend of academic robotics research and production-grade ML/system engineering.
11 years of coding experience
10 years of employment as a software developer
Graduate Degree Electronics Engineering, Graduate Degree Electronics Engineering at University of Buenos Aires
Master of Science (M. Sc) Automation & Robotics, Master of Science (M. Sc) Automation & Robotics at Universidad Politécnica de Madrid
Camera calibration, Dataset management, Run tracking, Parameter tuning, Camera inventory & your own Calibration Assistant—engineered for vision system pros.
Contributions:59 PRs, 60 pushes, 57 branches in 10 months
Contributions:40 pushes, 1 branch in 4 years 11 months
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