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Wekesa Timothy

Wekesa Timothy

AI Data Labeller / Annotator

USA flagIndianapolis, Usa
$20.00/hrIntermediateOther

Key Skills

Software

Other

Top Subject Matter

Large Language Model Evaluation
Legal Services & Contract Review
Regulatory Compliance & Risk Analysis

Top Data Types

TextText
ImageImage
DocumentDocument

Top Task Types

Bounding BoxBounding Box
ClassificationClassification
Entity (NER) ClassificationEntity (NER) Classification
SegmentationSegmentation

Freelancer Overview

AI Data Labeller / Annotator (Project-Based). Brings 1 year of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, Dedan Kimathi University of Technology (2018). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

IntermediateEnglishSwahili

Labeling Experience

AI Data Labeller / Annotator (Project-Based)

OtherText
As an AI Data Labeller/Annotator at Outlier AI, I labeled structured and unstructured datasets such as text prompts, image classifications, and conducted quality evaluation of responses. I followed detailed project guidelines, applied consistent tagging standards, and met strict annotation accuracy and productivity benchmarks. I provided structured feedback on ambiguous data to improve annotation clarity and the overall model training process. • Annotated and evaluated outputs generated by large language models. • Maintained data integrity and labeling consistency across projects. • Met productivity and quality targets under tight deadlines. • Improved feedback mechanisms for edge cases and unclear data samples.

As an AI Data Labeller/Annotator at Outlier AI, I labeled structured and unstructured datasets such as text prompts, image classifications, and conducted quality evaluation of responses. I followed detailed project guidelines, applied consistent tagging standards, and met strict annotation accuracy and productivity benchmarks. I provided structured feedback on ambiguous data to improve annotation clarity and the overall model training process. • Annotated and evaluated outputs generated by large language models. • Maintained data integrity and labeling consistency across projects. • Met productivity and quality targets under tight deadlines. • Improved feedback mechanisms for edge cases and unclear data samples.

2025 - 2026

Education

D

Dedan Kimathi University of Technology

Bachelor of Science, Electrical and Electronic Engineering

Bachelor of Science
2014 - 2018

Work History

N

Nyandarua National Polytechnic

Technical Trainer

Nyahururu
2022 - 2025
D

Dedan Kimathi University of Technology

Graduate Assistant

Nyeri
2019 - 2021