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Matteo SchröpferMS
Open to opportunities

Matteo Schröpfer

@matteoschrpfer

I improve German AI outputs through translation, evaluation, and linguistic quality control.

Germany
Message

What I'm looking for

I'm looking for opportunities to evaluate and improve German-language AI systems through translation, linguistic quality assurance, structured error analysis, and clear feedback in a collaborative remote environment.

At Micro1, I analyze and critique German AI model outputs for precision, logic, tone, contextual fit, and grammatical accuracy. I also construct and review German datasets and provide structured feedback that supports language model refinement.

I've translated and quality-checked German and English technical content for Outlier's AI training pipelines, conducting error analysis to ensure native fluency and contextual appropriateness.

At Babel Audio, I created and quality-checked German voice datasets for speech recognition and AI audio model training.

My background combines German language QA, translation, editing, grammar and syntax review, and reliable remote collaboration. I bring strong attention to detail, clear documentation, and a focus on improving language quality.

Experience

Work history, roles, and key accomplishments

MI
Current

German Language Expert

Micro1

Jun 2026 - Present (2 months)

Analyze, evaluate, and critique German AI model outputs with focus on precision, logic, tone, contextual fit, and grammatical accuracy. Perform structured linguistic quality control to identify semantic errors, unnatural phrasing, and stylistic inconsistencies.

BA

German Voice Data Contributor

Babel Audio

Jun 2026 - Jul 2026 (1 month)

Created and quality-checked German voice datasets to support speech recognition and AI audio model training. Maintained rigorous process discipline, linguistic accuracy, and quality-focused execution under project parameters.

Education

Degrees, certifications, and relevant coursework

GS

Gymnasium in Halle (Saale)

Abitur, Social Sciences and Languages

Completed Abitur with focus on Social Sciences and Languages, earning the Großes Latinum qualification.

Martin Luther Universität logoMU

Martin Luther Universität

Bachelor of Computer Science, Computer Science

2026 -

Grade: 2.3

Computer Science (AI Focus)
Core CS Fundamentals: Programming (Python, C++), algorithms, data structures, and database management.

Math Foundation: Linear algebra, calculus, probability, and statistics (the backbone of AI algorithms).

AI & Machine Learning: Supervised/unsupervised learning, deep learning, and neural networks (using PyTorch/TensorFlow).

Tech stack

Software and tools used professionally

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