Diana González-rico is a Data Engineer based in Mexico City with 11 years of experience building data-driven solutions and production ML tooling. She brings a strong research-to-production background from roles including an AI Residency at Facebook AI and current work at Human API, combining applied machine learning insights with robust data engineering practices. Trained in mathematics and AI at UNAM, she blends theoretical rigor with practical implementation—evident in her contributions to Facebook Research’s ParlAI where she improved training, self-chat capabilities, and testing for dialogue models. Comfortable across mobile, research, and backend domains, she has moved between iOS development and large-scale ML projects, which gives her a rare full-stack perspective on data products. Colleagues rely on her for thoughtful bug fixes, test-driven enhancements, and pragmatic feature additions that bridge research code and production systems.
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
Role in this project:
ML Engineer
Contributions:10 reviews, 11 commits, 21 PRs in 10 months
Contributions summary:Diana primarily contributed to the `parlai` repository by implementing and modifying code related to model training, self-chat functionality, and testing. They introduced features like reading classes from a file for a torch classifier agent and made updates to the self-chat script to support different models. The user also made improvements to existing components by adding tests, fixing bugs, and updating the code. Additionally, the user worked on wrapper teachers for handling data transformations and configurations.
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