Ahmet Melek
Software Engineer at unstructured.io
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolAhmet Melek is a software engineer based in London with 7 years of experience specializing in machine learning and NLP, currently building production ML systems at unstructured.io. He has hands-on expertise across the model lifecycle—from data annotation and custom NER to deployment, monitoring, and cost-conscious inference optimizations—gained at startups serving commercial and public sector clients. His background spans applied research (medical imaging and chemotherapy response prediction) and engineering for large-scale semantic search and information extraction, giving him both academic rigor and product-focused pragmatism. Notably, he designed a novel inference triage approach for relationship extraction to improve speed and efficiency in real-world pipelines.
7 years of coding experience
4 years of employment as a software developer
High School Diploma, Science, 93/100, High School Diploma, Science, 93/100 at Trabzon High School of ScienceBachelor of Business Administration - BBA, 3.70/4.00, Bachelor of Business Administration - BBA, 3.70/4.00 at Boğaziçi University
Stackoverflow
3reputation
204reached
0answers
1question
Github Skills (41)
labeling10
preprocessing10
data-pipelines10
data-science10
langchain10
ocr10
pdf-to-text10
pdf10
donut10
machine-learning10
docx10
information-retrieval10
ml10
llm10
mlops10
Programming languages (4)
Github contributions (5)
ahmetmeleq/Machine-Learning-System-Performance-Measurement
Mar 2019 - Feb 2025
This code makes you measure the performance of a similarity-score based face recognition (or any other recognition) system.
Contributions:1 PR, 3 pushes, 1 branch in 6 years
pythonsimilarity-scoreface-recognitionrecognitionsimilarity
ahmetmeleq/Applied-AI-Study-Group-2020
Feb 2020 - Mar 2020
This is the repository for the content of inzva 2020-February Applied AI Study Group, guided by Ahmet Melek.
Contributions:33 commits, 1 PR, 31 pushes in 1 month
deep-learningmachine-learningstudy-groupguidedartificial-intelligence
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