Matheus Pereira
Senior Software Development Engineer at Microsoft
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolMatheus Pereira is a Senior Software Development Engineer in Montreal with 11 years of experience and a Master’s in Artificial Intelligence focused on knowledge representation, semantic web and reasoning for learning environments. A Python specialist with deep expertise in backend and frontend stacks, he has shipped production ML services and Kubernetes-deployed workflows, leveraging Dask for parallelism and tools like TensorFlow, Keras and scikit-learn. His career spans startups and industry, including tech lead work at Stradigi AI and his current role at Microsoft, where he blends research collaboration with production-grade engineering. He has a strong track record designing high-availability microservices and data platforms using SQL/NoSQL, Cassandra, Redis and AWS, and brings practical DevOps and agile practices to delivery. Unusually for an SRE/ML engineer, his academic work and early projects emphasize semantic web and gamified learning systems, reflecting a rare combination of applied AI research and large-scale systems engineering.
11 years of coding experience
11 years of employment as a software developer
Bachelor of Science (B.Sc.), Computer Science, Bachelor of Science (B.Sc.), Computer Science at Universidade de Caxias do SulTécnico em Informática, Programação de Computadores, Técnico em Informática, Programação de Computadores at QI - Escolas e FaculdadesMaster's degree, Artificial Intelligence, Master's degree, Artificial Intelligence at Universidade Federal do Rio Grande do Sul
Portuguese, English
Stackoverflow
131reputation
3kreached
2answers
7questions
Github Skills (78)
python10
mlops10
pydata10
pandas10
llmops10
xpu10
transformer10
gpt10
llama10
amd10
dask10
cuda10
pytorch10
inference10
tpu10
Programming languages (6)
Github contributions (5)
microsoft/deep-language-networks
Jun 2023 - May 2024
We view Large Language Models as stochastic language layers in a network, where the learnable parameters are the natural language prompts at each layer. We stack two such layers, feeding the output of one layer to the next. We call the stacked architecture a Deep Language Network - DLN
Contributions:35 reviews, 35 PRs, 112 pushes in 10 months
TcheLinux/caxias
Sep 2015 - Jun 2017
Contributions:33 pushes, 2 branches in 1 year 9 months
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