Reuben Morais
Engineering Manager, Machine Learning at voize
Berlin, Germany
Summary
🤩
Rockstar🎓
Top SchoolReuben Morais is an engineering manager specializing in machine learning with 15 years of experience building and shipping speech and systems software from research to production. Based in Berlin, he has led teams and product-focused ML engineering at Voize after co-founding Coqui and delivering speech models and tooling at Mozilla, where he worked on DeepSpeech, TTS and Firefox OS. He combines hands-on DevOps, model engineering and front-end experience—improving build systems, CI, ARM packaging, and user-facing UI touches—so he understands both low-level infrastructure and product UX. An active open-source contributor, Reuben has improved widely used projects like Mozilla DeepSpeech and Coqui STT, notably adding batched decoder APIs and ClearML tracking integrations that accelerate real-world STT workflows.
15 years of coding experience
13 years of employment as a software developer
Industrial Informatics, Industrial Informatics at Centro Federal de Educação Tecnológica de Minas GeraisBachelor's degree Information Systems, Bachelor's degree Information Systems at Universidade Federal de Minas Gerais
Stackoverflow
1,022reputation
172kreached
23answers
4questions
Github Skills (39)
pytorch10
javascript10
python10
machine-learning10
text-to-speech10
mozilla-deepspeech10
uid10
deeplearning-ai10
deep-learning10
tensorflow10
front-end-development10
read-me10
speech-recognition10
devops10
documentation10
Programming languages (18)
Github contributions (5)
coqui-ai/STT
Jul 2021 - Sep 2022
🐸STT - The deep learning toolkit for Speech-to-Text. Training and deploying STT models has never been so easy.
Role in this project:
ML Engineer & DevOps Engineer
ML Engineer & DevOps EngineerContributions:4 releases, 90 reviews, 61 commits in 1 year 2 months
Contributions summary:Reuben primarily focused on improving the Speech-to-Text (STT) pipeline and associated tooling. Their contributions include adding a batched version of the decoder API for the wav2vec2 AM model, enhancing LM generation tracking with ClearML integration, and resolving build and dependency issues (e.g., broken static linking). Further contributions involved streamlining the build process for Linux ARM wheels, and optimizing CI configuration.
deep-learningspeech-to-textstttensorflowautomatic-speech-recognition
mozilla/DeepSpeech-examples
Dec 2019 - Feb 2021
Examples of how to use or integrate DeepSpeech
Role in this project:Technical Writer
Technical WriterContributions:68 commits, 21 PRs, 53 pushes in 1 year 2 months
Contributions summary:Reuben primarily focused on refining the documentation within the `mozilla/deepspeech-examples` repository. Their contributions involved updating the README files, correcting links, and improving the clarity of the examples, particularly for the v0.6.0 release. The modifications reflect an effort to enhance the user experience and provide more accessible guidance for integrating and using DeepSpeech. This included clarifying instructions for various branches and projects.
dotnetpythondeepspeechdeep-learningspeech-recognition
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