Gabriel Soto
Machine Learning Performance Engineer at Yokogawa Insilico Biotechnology gmbh
Chile
Summary
🤩
Rockstar🎓
Top SchoolGabriel Soto is a Machine Learning Performance Engineer with nine years of experience integrating ML and generative AI into production systems across logistics, transportation, energy, IoT, GPS and satellite imagery. He has a strong track record building scalable MLOps and GenAI platforms—designing RAG pipelines, inference deployment frameworks, and cost-aware LLM gateways—while driving change management and data culture in enterprise settings. Gabriel combines hands-on cloud and infra skills (GCP, Dataflow, Apache Beam, Kubeflow) with product-minded ML work that reduces overfitting, improves generalization, and delivers tangible cost and feature outcomes. He thrives in fuzzy roles, shaping product and team needs from the inside and translating business problems into reliable AI solutions. A graduate of Pontifical Catholic University of Chile, he also brings teaching and open-source community experience that informs his focus on reproducible, observable ML in production.
9 years of coding experience
5 years of employment as a software developer
Licencia De Enseñanza Media, Licencia De Enseñanza Media at Colegio Inglés de TalcaLicencia De Enseñanza Basica, Licencia De Enseñanza Basica at Colegio Concepcion de TalcaEngineering, Computer Science, Engineering, Computer Science at Pontifical Catholic University of Chile
Spanish, inglés b2
Github Skills (93)
visitors10
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chat-application10
generator10
scriptableobject10
django9
jwt9
gatsby9
unity3d9
socket9
epic9
chat9
backend9
react9
Programming languages (12)
Github contributions (5)
FarDust/FarDust
Nov 2020 - May 2022
Contributions:22 commits, 2 PRs, 20 pushes in 1 year 6 months
FarDust/fardust-web
Apr 2021 - Aug 2024
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Contributions:1 release, 5 reviews, 57 PRs in 3 years 4 months
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