School ZST mielec Informatic technichian
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I have comprehensive experience in the AI data pipeline, specializing in data labeling, annotation, and model training for advanced machine learning projects. A significant portion of my background includes working on cutting-edge AI speech translation systems, where I contributed to both speech-to-text and speech-to-speech localization frameworks. My responsibilities involved meticulous audio transcription, semantic alignment, and language modeling to ensure high-fidelity datasets. By rigorously applying complex annotation guidelines, I helped improve the acoustic and linguistic accuracy of models handling diverse dialects and cultural nuances. Throughout these projects, I have mastered standard data hygiene practices, iterative feedback loops, and quality assurance workflows essential for natural language processing (NLP). I am highly skilled at identifying edge cases, resolving ambiguities in source data, and collaborating effectively within remote, cross-functional teams of engineers and language specialists. This hands-on experience has equipped me with the analytical precision needed to deliver clean, structured training data that directly enhances model performance, scalability, and automated evaluation metrics.
Degree not specified
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