Adam Klimek

Key Skills

Software

Appen

Mercor

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Video

Top Task Types

Action Recognition

Audio Recording

Classification

Data Collection

Evaluation Rating

Prompt Response Writing SFT

RLHF

Text Generation

Text Summarization

Transcription

Translation Localization

Freelancer Overview

I have hands-on experience developing and refining high-quality training data for AI models, particularly in mathematics and general knowledge domains. My role as a Data Quality Specialist at Outlier AI involved creating unique prompts, auditing AI-generated responses, and selecting optimal outputs to ensure data accuracy, clarity, and reliability. I am skilled at analyzing and evaluating large datasets, collaborating with AI development teams, and providing structured feedback to improve model performance and consistency. My strong analytical mindset, attention to detail, and proficiency with tools like MS Office, as well as my ability to work independently or in teams, enable me to contribute effectively to data labeling and annotation projects across diverse domains.

Labeling Experience

AI Data Reviewer (Transcription QA + Linguistic Quality)

AppenAudioClassification

Reviewed and corrected French and English audio transcriptions for AI speech-recognition training datasets. Ensured all segmentations, punctuation, and formatting met strict annotation and linguistic quality guidelines. Documented issues for standardization and applied systematic corrections across a large workload. • Maintained accuracy when aligning audio with text. • Applied consistent annotation criteria at high scale. • Corrected and verified segmentation of transcription labels. • Ensured detailed, high quality review of each dataset entry.

Reviewed and corrected French and English audio transcriptions for AI speech-recognition training datasets. Ensured all segmentations, punctuation, and formatting met strict annotation and linguistic quality guidelines. Documented issues for standardization and applied systematic corrections across a large workload. • Maintained accuracy when aligning audio with text. • Applied consistent annotation criteria at high scale. • Corrected and verified segmentation of transcription labels. • Ensured detailed, high quality review of each dataset entry.

2024

Data Quality Specialist – AI Training (Evaluation, Labeling, Prompting)

MercorTextEvaluation Rating

Evaluated and verified labeled items and AI-generated answers, focusing on classification, question answering, and text generation tasks. Applied detailed rubrics and project guidelines to assess instruction-following, clarity, and accuracy. Performed labeling, prompt engineering, and quality control for high-quality text datasets used in AI model development. • Ensured taxonomy and label consistency at scale. • Documented rationale for all revisions and escalated ambiguous edge cases. • Extracted and referenced relevant text from image-based items for Q&A validation. • Iterated on prompts to improve model reliability and task clarity.

Evaluated and verified labeled items and AI-generated answers, focusing on classification, question answering, and text generation tasks. Applied detailed rubrics and project guidelines to assess instruction-following, clarity, and accuracy. Performed labeling, prompt engineering, and quality control for high-quality text datasets used in AI model development. • Ensured taxonomy and label consistency at scale. • Documented rationale for all revisions and escalated ambiguous edge cases. • Extracted and referenced relevant text from image-based items for Q&A validation. • Iterated on prompts to improve model reliability and task clarity.

2024

Education

Work History