Daniel Nouri
AI Consultant at Aldeology Consulting AB
Malmo, Sweden
Summary
🤩
Rockstar🎓
Top SchoolDaniel Nouri is an AI engineer and seasoned machine learning practitioner with 20 years of experience delivering production-ready ML systems, from edge inference to large-language-model workflows. Based in Malmö, Sweden, he has led ML teams and initiatives at enterprises like Securitas and AT&T and founded a consultancy that shipped solutions across finance, medical imaging, and OCR. He is a prolific open-source contributor and co-author of widely used projects such as nolearn and skorch, with deep involvement in testing, documentation, and deployment examples that bridge research and production. Daniel combines strong backend and cloud engineering experience (cloud-custodian, Colander, Deform) with practical evaluation frameworks for LLMs and automated testing, often working closely with domain experts to ensure correctness. Known for building tooling and processes as much as models, he brings a pragmatic, iterative approach to turning complex ML research into reliable business value.
20 years of coding experience
18 years of employment as a software developer
Computer Science, Computer Science at Technical University of MunichSuccessfully completed Machine Learning, Successfully completed Machine Learning at Coursera - Stanford UniversitySuccessfully completed Neural Networks for Machine Learning, Successfully completed Neural Networks for Machine Learning at Coursera - University of Toronto
Stackoverflow
1,264reputation
119kreached
23answers
0questions
Github Skills (64)
unit-testing10
web-widgets10
datetime10
pytorch10
cloud-computing10
python10
validations10
widgets10
data-science10
scikit10
testing10
deform10
machine-learning10
data-serialization10
datetimes10
Programming languages (15)
Github contributions (5)
dnouri/nolearn
Nov 2012 - Nov 2019
Combines the ease of use of scikit-learn with the power of Theano/Lasagne
Role in this project:
Data Scientist / ML Engineer
Data Scientist / ML EngineerContributions:318 commits, 165 PRs, 233 pushes in 7 years
Contributions summary:Daniel contributed significantly to the `nolearn` repository, focused on machine learning and deep learning tasks. Their work involved implementing and improving DBN (Deep Belief Network) models, adding features like pretrain and finetune callbacks and the ability to handle regression tasks. They made modifications to the codebase, including adjustments to dataset handling, and also contributed to documentation.
lasagnescikit-learntheanodeep-learningmachine-learning
Lasagne/Lasagne
Sep 2014 - Sep 2015
Lightweight library to build and train neural networks in Theano
Role in this project:ML Engineer
ML EngineerContributions:49 commits, 10 PRs, 159 comments in 11 months
Contributions summary:Daniel contributed to building and improving a neural network library in Theano. They added build scripts, and set up unit tests, and improved the example by restructuring the code, adding new examples. The user also addressed a bug in the library's crossentropy function. The contributions demonstrate a focus on library usability and testing of machine learning components.
neural-networktheanodeep-learning-libraryneural-networkspython
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