Maureen Wanjiru

Key Skills

Software

Labelbox

CVAT

Appen

Clickworker

Data Annotation Tech

Encord

HiveMind

Mercor

Micro1

OneForma

Mindrift

Remotasks

Toloka

Telus

Top Subject Matter

Natural Language Processing (NLP)

Sentence Classification

Sentiment Analysis

Top Data Types

Text

Image

Document

Top Task Types

Classification

Object Detection

Text Generation

Data Collection

Prompt Response Writing SFT

Freelancer Overview

Data Annotation Specialist (NLP, Text). Core strengths include Labelbox and CVAT. AI-training focus includes data types such as Text and Image and labeling workflows including Classification and Object Detection.

Labeling Experience

AI Text Annotation Specialist

TextQuestion Answering

This project focused on training AI models to generate accurate and contextually appropriate answers to user questions. My responsibilities included annotating datasets by identifying intent, ranking response quality, correcting inaccuracies, and providing clear, structured feedback to improve answer precision. I worked with diverse topics, ensured consistency across annotations, and helped optimize the model’s ability to understand and respond naturally to real-world queries.

This project focused on training AI models to generate accurate and contextually appropriate answers to user questions. My responsibilities included annotating datasets by identifying intent, ranking response quality, correcting inaccuracies, and providing clear, structured feedback to improve answer precision. I worked with diverse topics, ensured consistency across annotations, and helped optimize the model’s ability to understand and respond naturally to real-world queries.

2022 - Present

Image and Data Annotation Specialist (Computer Vision)

CVATImageObject Detection

I participated in image annotation projects for visual recognition systems, focusing on labeling objects, drawing bounding boxes, and creating segmentation masks. Consistency was maintained across thousands of images to support computer vision model training. Annotation timelines were tight, requiring attention to detail and accuracy throughout the process. • Used multiple annotation platforms including CVAT and Scale AI. • Labeled various object categories across diverse visual datasets. • Documented challenging cases to reduce labeling inconsistencies. • Helped improve computer vision models through precise annotation work.

I participated in image annotation projects for visual recognition systems, focusing on labeling objects, drawing bounding boxes, and creating segmentation masks. Consistency was maintained across thousands of images to support computer vision model training. Annotation timelines were tight, requiring attention to detail and accuracy throughout the process. • Used multiple annotation platforms including CVAT and Scale AI. • Labeled various object categories across diverse visual datasets. • Documented challenging cases to reduce labeling inconsistencies. • Helped improve computer vision models through precise annotation work.

2020 - Present

Data Annotation Specialist (NLP, Text)

LabelboxTextClassification

I contributed to training datasets for NLP models by performing data labeling and annotation tasks on various text data. My work involved classification, sentiment analysis, entity recognition, and paraphrasing to enhance training quality and diversity. I ensured high levels of accuracy through annotation review and refined text to maintain clarity and engagement. • Reviewed and corrected annotations as part of quality control. • Adapted quickly to new guidelines and annotation tools per project. • Edited both AI-generated and human-written text for model training. • Met deadlines in fast-paced, distributed team environments.

I contributed to training datasets for NLP models by performing data labeling and annotation tasks on various text data. My work involved classification, sentiment analysis, entity recognition, and paraphrasing to enhance training quality and diversity. I ensured high levels of accuracy through annotation review and refined text to maintain clarity and engagement. • Reviewed and corrected annotations as part of quality control. • Adapted quickly to new guidelines and annotation tools per project. • Edited both AI-generated and human-written text for model training. • Met deadlines in fast-paced, distributed team environments.

2020 - Present

Education

Work History