Martín Cooper
Software Engineer at IBM
Vicente López, Buenos Aires, Argentina
Summary
👤
Senior🎓
Top SchoolMartín Cooper is a full-stack software engineer with nine years of experience, currently building AI automation and interactive AI tools with IBM Research. He combines cloud-native practices (Docker, Kubernetes, IBM Cloud CI/CD) with web frameworks (Flask, Spring Boot, React) and production data stores like COS and MongoDB to take research prototypes toward deployable systems. As maintainer of EvalAssist and Label Sleuth, he contributes to practical ML tooling that bridges model evaluation and labeling workflows. Educated in Argentina and with study experience at Université de Montpellier, he brings an international, research-adjacent perspective and a knack for turning experimental AI ideas into reliable, user-facing services.
10 years of coding experience
1 year of employment as a software developer
Information et Gestion, Computer Science, Information et Gestion, Computer Science at Université de MontpellierSoftware Engineer, Software Engineering, Software Engineer, Software Engineering at National University of the Center of Buenos Aires Province
Github Skills (61)
transformers10
pytorch10
javascript10
python10
evaluation10
no-code10
benchmarking10
text-classification10
text-annotation10
datasets10
classifiers10
ai10
natural-language-processing10
nlp10
react10
Programming languages (6)
Github contributions (5)
martinscooper/tesis
May 2020 - May 2025
Contributions:14 pushes, 1 branch in 5 years
IBM/eval-assist
May 2025 - Nov 2025
EvalAssist is an open-source project that simplifies using large language models as evaluators (LLM-as-a-Judge) of the output of other large language models by supporting users in iteratively refining evaluation criteria in a web-based user experience.
Contributions:34 releases, 2 reviews, 104 PRs in 6 months
large-language-modelsllm
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