Manuel Hidalgo
Software Engineer - Ai Infrastructure @Meta
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WORK HISTORY
Software Engineer - Ai Infrastructure @Meta
Streamlined communications by developing a tool that automatically posts critical infrastructure announcements directly onto engineer\'s job failure screens, which significantly reduced the number of repetitive support questions on internal groups. Defined the long-term project roadmap, including the development of automated features to detect major system incidents and prompt on-call teams to create announcements. Led and contributed to the Guided Enablement project, delivering a streamlined setup experience for online and recurring model training. Designed and proposed a reliable, unified package selection mechanism and clear registration flow, resolving fragmented setup processes and a non-durable architecture for model training frameworks. Engineered a core platform capability to automate bad data exclusion, streamlining the high-priority data quality incident recovery process and accelerating the model correction and re-launch cycle. Developed and deployed foundational software features (create, view, delete data exclusion rules) to ensure system reliability and broad compatibility across all product groups and engineering platforms. Built scalable, user-centric ML tools and visualizations, significantly driving adoption and measurable impact across AI/GenAI teams. Led UI/UX enhancements for logging and model-understanding tools, improving data observability and ML engineer efficiency. Migrated charting infrastructure from Highcharts to Vega-Lite and Chart.js, modernizing large-scale ML visualization and enabling advanced interactions (zooming, sampling). Developed dynamic analyzers and metrics dashboards to streamline custom ML debugging, error detection, and performance evaluation. Modernized legacy systems, improving data accuracy, reducing latency, and enhancing user engagement with innovative solutions. Coordinated end-to-end execution of high-impact initiatives, including beta launches, RFC cycles, and cross-team adoption efforts.
EDUCATION
Rochester Institute of Technology
Master of Science, Industrial Engineering - Statistical Data Analysis
Universidad de Costa Rica UCR
Associate’s degree, Computer Networks
Universidad de Costa Rica UCR
Bachelor's degree, Computer Science
Universidad Fidélitas
Specialty in Notary and Registry Law, Law
Universidad Santa Lucía
Licenciatura, Law
SKILLS
ABOUT MANUEL HIDALGO
I’m a data-driven engineer with a career spanning data pipelines, ETL, and predictive modeling to building scalable machine learning and AI systems. My experience ranges from regression research and distributed simulations to deploying forecasting and sentiment analysis models, and more recently, to designing ML infrastructure that enables robust A/B testing, observability, and debugging across distributed clusters. I’ve led initiatives that modernized visualization platforms, improved model health monitoring, and streamlined experimentation cycles, driving adoption of AI/GenAI tools across teams. At the intersection of engineering, data science, and product strategy, I focus on creating AI systems that are reliable, scalable, and impactful.
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