Amon Kiprotich

Key Skills

Software

Label Studio

CVAT

Other

Top Subject Matter

E-commerce product reviews/sentiment analysis

Autonomous driving/traffic object detection

Named Entity Recognition (NER) for news articles

Top Data Types

Text

Image

Top Task Types

Classification

Bounding Box

Entity (NER) Classification

RLHF

Freelancer Overview

Sentiment Annotation Pipeline: Sentiment Data Labeler. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio, CVAT, and Other. Education includes Specialist Program Certificate, AI Training Academy (2025) and Bachelor of Science, KCA University (2023). AI-training focus includes data types such as Text and Image and labeling workflows including Classification, Bounding Box, and Entity (NER) Classification.

Labeling Experience

AI Training Specialist Program Graduate (AI Training Academy)

TextRLHF

I completed a specialist program centered on quality data labeling for large language models (LLMs), segmentation, and audio transcription. Through hands-on projects, I was trained in reinforcement learning from human feedback (RLHF) frameworks and best quality assurance methods. I practiced high-fidelity labeling using real-world examples to enhance AI training data. • Participated in comprehensive AI data training modules • Labeled varied data types, including text, images, and audio • Focused on RLHF tasks for LLMs and related systems • Learned quality assurance and advanced annotation techniques

I completed a specialist program centered on quality data labeling for large language models (LLMs), segmentation, and audio transcription. Through hands-on projects, I was trained in reinforcement learning from human feedback (RLHF) frameworks and best quality assurance methods. I practiced high-fidelity labeling using real-world examples to enhance AI training data. • Participated in comprehensive AI data training modules • Labeled varied data types, including text, images, and audio • Focused on RLHF tasks for LLMs and related systems • Learned quality assurance and advanced annotation techniques

2025 - 2025

NER Data Preparation: NER Dataset Creator

OtherTextEntity Ner Classification

I created a named entity recognition (NER) dataset from news articles, labeling entities like PERSON, ORG, and LOC. Using Python and annotation tools, I ensured annotation consistency and exported the dataset in the standardized CoNLL format for easy use in model training. My work helped prepare data for NER research and machine learning projects. • Extracted and labeled entities in unstructured text • Applied NER guidelines for high-quality annotation • Used Python scripting for validation and export • Focused on news/media dataset preparation

I created a named entity recognition (NER) dataset from news articles, labeling entities like PERSON, ORG, and LOC. Using Python and annotation tools, I ensured annotation consistency and exported the dataset in the standardized CoNLL format for easy use in model training. My work helped prepare data for NER research and machine learning projects. • Extracted and labeled entities in unstructured text • Applied NER guidelines for high-quality annotation • Used Python scripting for validation and export • Focused on news/media dataset preparation

2024 - 2024

Object Detection (CVAT): Image Bounding Box Annotator

CVATImageBounding Box

I labeled over 500 traffic images with bounding boxes, identifying and classifying objects such as cars, persons, and bicycles using CVAT software. My annotations contributed to a simulated dataset for autonomous driving model development. I adhered to strict quality guidelines to ensure accurate and reliable data for computer vision tasks. • Labeled images for object detection models • Used the CVAT platform extensively • Followed best practices for bounding box annotation • Contributed to autonomous vehicle dataset creation

I labeled over 500 traffic images with bounding boxes, identifying and classifying objects such as cars, persons, and bicycles using CVAT software. My annotations contributed to a simulated dataset for autonomous driving model development. I adhered to strict quality guidelines to ensure accurate and reliable data for computer vision tasks. • Labeled images for object detection models • Used the CVAT platform extensively • Followed best practices for bounding box annotation • Contributed to autonomous vehicle dataset creation

2024 - 2024

Sentiment Annotation Pipeline: Sentiment Data Labeler

Label StudioTextClassification

I annotated over 1,000 product reviews for sentiment, labeling them as positive, negative, or neutral using Label Studio. I developed detailed guidelines, resolved annotation edge cases, and achieved a high level of consistency with 95% inter-annotator agreement. My work directly improved the quality and usability of the dataset for downstream sentiment analysis models. • Responsible for all aspects of the annotation workflow • Ensured high quality through self-review and collaboration • Utilized Label Studio as the main annotation platform • Focused on clear guideline development and edge case resolution

I annotated over 1,000 product reviews for sentiment, labeling them as positive, negative, or neutral using Label Studio. I developed detailed guidelines, resolved annotation edge cases, and achieved a high level of consistency with 95% inter-annotator agreement. My work directly improved the quality and usability of the dataset for downstream sentiment analysis models. • Responsible for all aspects of the annotation workflow • Ensured high quality through self-review and collaboration • Utilized Label Studio as the main annotation platform • Focused on clear guideline development and edge case resolution

2024 - 2024

Education

Work History