Dennis W.

Key Skills

Software

Appen

Clickworker

CVAT

Data Annotation Tech

Label Studio

OneForma

Remotasks

Scale AI

SuperAnnotate

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Task Types

Classification

Data Collection

Evaluation/Rating

Mapping

Text Generation

Freelancer Overview

I have extensive experience in data labeling and AI training, working with text, audio, image, and video data. I have evaluated chatbot responses, performed search quality assessments, and annotated datasets to help train AI systems. My work emphasizes accuracy, consistency, and adherence to complex guidelines, ensuring high-quality training data for machine learning projects. I am skilled in handling diverse data types and projects, including satellite image classification, LLM evaluation, and media processing. I consistently meet deadlines in remote work settings and provide clear, actionable feedback to improve AI performance. My combination of technical skills, attention to detail, and reliability sets me apart as a proficient contributor to AI training initiatives.

Labeling Experience

Computer Vision Dataset Creation

OneFormaImageBounding BoxSegmentation

Worked on a computer vision project involving large-scale image annotation to train AI models for object detection and segmentation. Tasks included drawing bounding boxes, labeling objects, and performing pixel-level segmentation to accurately define object boundaries. The dataset included thousands of images across multiple categories, requiring consistent application of labeling standards. Quality measures included regular cross-checks, adherence to strict annotation guidelines, and validation to ensure high accuracy and consistency. Key Skills: Image annotation, object detection, segmentation, bounding box labeling, guideline interpretation, quality assurance Impact: Produced high-quality annotated datasets that improved model accuracy, detection performance, and overall reliability of AI vision systems.

2022 - 2025

Conversational AI

TolokaTextText GenerationText Summarization

Worked on a large-scale conversational AI project to train and improve a large language model. The project involved labeling thousands of chatbot responses for relevance, accuracy, tone, and clarity. Specific tasks included categorizing responses, flagging inappropriate or ambiguous outputs, and ensuring alignment with predefined guidelines. The dataset spanned multiple domains and required consistent application of labeling standards across all entries. Quality measures included cross-checking annotations, adhering to strict accuracy thresholds, and maintaining high inter-annotator agreement. Delivered outputs met or exceeded project quality benchmarks while completing tasks within tight deadlines. Key Skills: Text annotation, LLM evaluation, guideline interpretation, quality assurance, Toloka proficiency Impact: Enhanced the AI model’s response quality and reliability, contributing to better conversational performance and overall model accuracy.

2022 - 2024

Education

Work History