Recep Sarıtekin
AI Engineer at Timeless NYC
Antalya, Türkiye Turkey
Summary
🤩
Rockstar🎓
Top SchoolRecep Sarıtekin is an AI engineer and founder with nine years of experience building production-ready ML systems, from NLP pipelines and MLOps to voice cloning and multilingual dubbing products. He has a strong open-source pedigree—contributing dataset integrations and test automation to tensorflow/datasets—and combines hands-on backend engineering with research-driven model work. As founder of dublab.app and a founding AI engineer at NexStrat.ai, he turns cutting-edge models into user-facing features like one-click dubbing across 17 languages while preserving emotional nuance. Comfortable across TensorFlow, PyTorch, spaCy and deployment tooling, he has repeatedly moved projects from prototype to scalable service. Based in Antalya, Turkey, Recep brings an uncommon blend of product-focused entrepreneurship and deep implementation experience, often tackling ML as one piece of a broader systems challenge.
9 years of coding experience
4 years of employment as a software developer
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Muğla Sıtkı Koçman Üniversitesi
English, French, Turkish
Stackoverflow
88reputation
17kreached
3answers
0questions
Github Skills (16)
datasets10
testing10
machine-learning10
tensorflow10
python10
data-model10
user-data10
data-set10
numpy8
git6
version-control6
bitcoin6
git-checkout6
git-branch6
blockchain6
Programming languages (18)
Github contributions (5)
tensorflow/datasets
Mar 2019 - Aug 2019
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Role in this project:
Backend Developer & Test Automation Engineer
Backend Developer & Test Automation EngineerContributions:1 review, 70 commits, 42 PRs in 5 months
Contributions summary:Recep primarily contributed to the addition of the KMNIST and EMNIST datasets to the `tensorflow/datasets` repository. Their work included the creation of the necessary dataset files, the integration of the new datasets into the image module, and the implementation of corresponding tests. Furthermore, the user addressed issues related to the Kaggle downloader and corrected test utility mock files, showcasing their proficiency in data handling and testing procedures.
datanumpydeep-learningdatasetmachine-learning
hemreari/easy-comment
Nov 2017 - Jan 2023
Contributions:1 PR, 1 comment, 11 issues in 5 years 3 months
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