David Cuadrado
Bogota, RAP (Especial) Central, Colombia
Summary
🤩
Rockstar🎓
Top SchoolDavid Cuadrado is an experienced Principal Engineer with 18 years building backend-first systems across web, mobile and desktop platforms from Bogotá, Colombia. A systems engineer trained at Universidad del Valle, he blends deep Go and Ruby expertise with practical performance-minded engineering—evident from contributions to high-profile projects like TechEmpower’s FrameworkBenchmarks and machine-learning work in Gorgonia. He has hands-on experience building monitoring exporters, optimizing JSON/database paths, and implementing ML ops primitives such as sparsemax, showing comfort across infrastructure, data and model code. Colleagues rely on him to tackle tricky integration and performance problems, and his track record includes improving cross-platform libraries (image processing and Mongo mappers) and enhancing Windows compatibility. Notably, he often focuses on low-level, performance-sensitive layers that yield outsized system improvements.
18 years of coding experience
system engineer, Computer Science, system engineer, Computer Science at Universidad del Valle (CO)
English, Spanish
Github Skills (48)
json10
benchmark10
frameworkbenchmarks10
object-mapping10
operation10
back-end-development10
image-processing10
tensorrt10
associations10
app-framework10
machine-learning10
benchmarking10
differentiation10
mongodb-database10
ruby10
Programming languages (13)
Github contributions (5)
dcu/mongodb_exporter
Feb 2015 - May 2018
MongoDB exporter for prometheus.io
Role in this project:
Back-end Developer
Back-end DeveloperContributions:72 commits, 34 PRs, 65 pushes in 3 years 4 months
Contributions summary:David primarily focused on developing a MongoDB exporter for Prometheus, implementing core functionalities. The contributions involved creating the basic exporter, adding a collector package, and introducing a Group struct for organizing metrics. Further development included integrating server status data collection and implementing the collection of data, along with the introduction of configurable settings for the MongoDB connection. The work indicates a strong focus on back-end development and monitoring using Go.
exportermongodb-exporterprometheus-exporterprometheusmetrics
gorgonia/gorgonia
Oct 2020 - Jul 2022
Gorgonia is a library that helps facilitate machine learning in Go.
Role in this project:ML Engineer
ML EngineerContributions:9 reviews, 116 commits, 28 PRs in 1 year 9 months
Contributions summary:David's primary contribution focused on implementing and optimizing the "sparsemax" operation, a key component likely within a machine learning library. This involved writing the core sparsemax function, including the necessary mathematical calculations and support for different data types, and then implementing the required backpropagation logic, indicating a focus on model training and differentiation. Furthermore, the user created test cases to ensure the function's accuracy and integrated the operation within the Gorgonia framework.
golangcomputation-graphautomatic-differentiationdeep-learningdifferentiation
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