Diego De Las Casas
Artificial Intelligence Engineer at Mistral AI
United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolDiego De Las Casas is an Artificial Intelligence Engineer with 12 years of experience bridging research and production-grade ML, currently building at Mistral AI after six years as a Research Engineer at DeepMind. He has deep hands-on expertise in TensorFlow-based tooling and reinforcement learning, evidenced by contributions to high-profile DeepMind open-source projects like Sonnet, TRFL and deepmind-research where he handled versioning, Python3 migration, tests and releases. With a master's in computer science and an earlier background in psychology and cognitive research, he brings a rare mix of algorithmic rigor and human-centered insight to model development and evaluation. Colleagues rely on him for practical maintenance of complex ML codebases and for turning research prototypes into robust, reproducible artifacts.
12 years of coding experience
15 years of employment as a software developer
Escola Técnica de Formação Gerencial - ETFG/SEBRAEMaster's degree Computer Science, Master's degree Computer Science at Universidade Federal de Minas Gerais
Portuguese, English, German, Spanish
Stackoverflow
21reputation
169reached
0answers
2questions
Github Skills (23)
artificial-neural-networks10
python10
scripting10
testing10
machine-learning10
reinforcement-learning10
deeplearning-ai10
script10
deep-learning10
tensorflow10
neural-network10
sh10
shell10
develop9
build-system9
Programming languages (3)
Github contributions (5)
google-deepmind/trfl
Jun 2018 - Aug 2021
TensorFlow Reinforcement Learning
Role in this project:
ML Engineer
ML EngineerContributions:23 commits, 9 pushes, 7 comments in 3 years 2 months
Contributions summary:Diego contributed to the TensorFlow Reinforcement Learning (TRFL) library, making changes related to testing, adding license headers, and improving the build process. They modified test cases, including those for `indexing_ops` and `distribution_ops`, and updated dependencies. The user also added versioning to the library and made updates to support TensorFlow 2 and Python 3.7, as well as addressed issues related to numerical tolerances in the tests.
reinforcement-learningreinforcementdeep-reinforcement-learningtensorflow
google-deepmind/deepmind-research
Sep 2019 - Feb 2022
This repository contains implementations and illustrative code to accompany DeepMind publications
Role in this project:ML Engineer
ML EngineerContributions:16 commits, 41 PRs, 192 pushes in 2 years 5 months
Contributions summary:Diego primarily focused on minor maintenance and release-related tasks within the DeepMind research repository. Their contributions include small fixes to license headers, updates to shell scripts related to transporter and IODINE, and releasing the IODINE project. The commits showcase interaction with various project files, including configuration updates and code modifications within shell scripts and Jupyter notebooks.
pytorchimplementationsdeep-learningneural-networksmachine-learning
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