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I am a results-driven AI data specialist with over five years of hands-on experience across the full data lifecycle—from collection and preprocessing through annotation, evaluation, and quality assurance. I thrive in collaborative, detail-oriented environments where accuracy and privacy matter.\n\nWith dual training in Computer Science and English Studies, I blend technical rigor with linguistic sensitivity to deliver high-integrity training data for large language models, virtual assistants, and multimodal AI systems. I excel at pairwise comparisons, object tagging, intent classification, and structured feedback workflows. I am committed to creating responsible, unbiased AI data that meaningfully improves model performance.…I am a results-driven AI data specialist with over five years of hands-on experience across the full data lifecycle—from collection and preprocessing through annotation, evaluation, and quality assurance. I thrive in collaborative, detail-oriented environments where accuracy and privacy matter.\n\nWith dual training in Computer Science and English Studies, I blend technical rigor with linguistic sensitivity to deliver high-integrity training data for large language models, virtual assistants, and multimodal AI systems. I excel at pairwise comparisons, object tagging, intent classification, and structured feedback workflows. I am committed to creating responsible, unbiased AI data that meaningfully improves model performance.

Alud Alteme

Data Scientist, Data Analyst, Data Annotator, +2

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I am a results-driven AI data specialist with over five years of hands-on experience across the full data lifecycle—from collection and preprocessing through annotation, evaluation, and quality assurance. I thrive in collaborative, detail-oriented environments where accuracy and privacy matter.\n\nWith dual training in Computer Science and English Studies, I blend technical rigor with linguistic sensitivity to deliver high-integrity training data for large language models, virtual assistants, and multimodal AI systems. I excel at pairwise comparisons, object tagging, intent classification, and structured feedback workflows. I am committed to creating responsible, unbiased AI data that meaningfully improves model performance.…I am a results-driven AI data specialist with over five years of hands-on experience across the full data lifecycle—from collection and preprocessing through annotation, evaluation, and quality assurance. I thrive in collaborative, detail-oriented environments where accuracy and privacy matter.\n\nWith dual training in Computer Science and English Studies, I blend technical rigor with linguistic sensitivity to deliver high-integrity training data for large language models, virtual assistants, and multimodal AI systems. I excel at pairwise comparisons, object tagging, intent classification, and structured feedback workflows. I am committed to creating responsible, unbiased AI data that meaningfully improves model performance.

Available to hire

I am a results-driven AI data specialist with over five years of hands-on experience across the full data lifecycle—from collection and preprocessing through annotation, evaluation, and quality assurance. I thrive in collaborative, detail-oriented environments where accuracy and privacy matter.\n\nWith dual training in Computer Science and English Studies, I blend technical rigor with linguistic sensitivity to deliver high-integrity training data for large language models, virtual assistants, and multimodal AI systems. I excel at pairwise comparisons, object tagging, intent classification, and structured feedback workflows. I am committed to creating responsible, unbiased AI data that meaningfully improves model performance.

Skills

Prompt Engineering

Python

Experience Level

Prompt Engineering

Expert

Python

Expert

Language

English

Fluent

Work Experience

AI Data Specialist at Mindrift (Toloka AI)

February 1, 2024 - December 1, 2025

Executed end-to-end annotation workflows across text, audio, image, and video datasets with quality scores above 97%. Performed structured pairwise comparisons of AI outputs against rubrics for accuracy, relevance, fluency, and safety. Carried out object tagging and content labeling across media formats to support multimodal model training. Contributed to data collection by generating and validating synthetic dialogue samples for fine-tuning. Applied counting and segmentation tasks to image and video datasets for object-level supervision. Collaborated with project leads to interpret guidelines and surface edge cases, informing guideline revisions. Mentored onboarding annotators to reduce ramp-up time and improve labeling consistency. Maintained GDPR data privacy compliance.

AI Data Annotator at Outlier AI

January 1, 2022 - December 1, 2023

Annotated and evaluated text and speech datasets for AI applications spanning customer support automation and intelligent virtual assistants. Specialized in dialogue-level evaluation, assessing conversational coherence, intent alignment, and response quality. Participated in targeted bias detection for voice recognition, with focus on regional dialects and non-standard accents. Contributed to QA audits of annotated outputs, identifying systematic errors and recommending process improvements that reduced rework rates. Worked with linguists and ML engineers to refine labeling taxonomies for emotion and intent classification.