Trevor Allen

Key Skills

Software

Appen

Labelbox

CVAT

Other

Top Subject Matter

Computer Vision

Speech Recognition

Natural Language Processing

Top Data Types

Text

Image

Video

Audio

Top Label Types

Polyline

Object Detection

Tracking

Transcription

Freelancer Overview

AI Training Specialist / Data Annotation Specialist. Core strengths include Labelbox, CVAT, and Audacity. AI-training focus includes data types such as Image, Video, and Audio and labeling workflows including Object Detection, Tracking, and Transcription.

Labeling Experience

AI Training Specialist / Data Annotation Specialist

OtherText

As part of my role, I handled text data for prompt evaluation, response ranking, and sentiment analysis. Responsibilities included text classification, annotating AI-generated responses, and reviewing quality. I consistently maintained detailed annotation records and met project KPIs. • Evaluated and labeled text prompts and AI responses. • Conducted sentiment analysis and quality review. • Used Google Sheets and Excel for annotation tracking. • Ensured prompt turnaround to support project timelines.

As part of my role, I handled text data for prompt evaluation, response ranking, and sentiment analysis. Responsibilities included text classification, annotating AI-generated responses, and reviewing quality. I consistently maintained detailed annotation records and met project KPIs. • Evaluated and labeled text prompts and AI responses. • Conducted sentiment analysis and quality review. • Used Google Sheets and Excel for annotation tracking. • Ensured prompt turnaround to support project timelines.

2023 - Present

AI Training Specialist / Data Annotation Specialist

AudioTranscription

I performed audio transcription and speech labeling to assist in training AI speech recognition systems. Projects included speaker labeling, speech-to-text validation, and audio classification. Consistent quality and adherence to guidelines were key priorities throughout this work. • Transcribed English speech data for training datasets. • Used Audacity and speech-to-text validation platforms for annotation. • Classified audio files by voice type and quality. • Ensured high annotation fidelity by following review protocols.

I performed audio transcription and speech labeling to assist in training AI speech recognition systems. Projects included speaker labeling, speech-to-text validation, and audio classification. Consistent quality and adherence to guidelines were key priorities throughout this work. • Transcribed English speech data for training datasets. • Used Audacity and speech-to-text validation platforms for annotation. • Classified audio files by voice type and quality. • Ensured high annotation fidelity by following review protocols.

2023 - Present

AI Training Specialist / Data Annotation Specialist

CVATVideoTracking

I labeled video datasets including bounding boxes, object tracking, and activity recognition. My responsibilities included frame-by-frame annotation and ensuring activity labels adhered to project guidelines. I worked to meet accuracy standards through diligent review and collaboration. • Performed object tracking and activity recognition on video data. • Used CVAT and V7 Darwin for video label management. • Conducted quality assurance and peer reviews. • Created detailed annotation documentation to standardize workflow.

I labeled video datasets including bounding boxes, object tracking, and activity recognition. My responsibilities included frame-by-frame annotation and ensuring activity labels adhered to project guidelines. I worked to meet accuracy standards through diligent review and collaboration. • Performed object tracking and activity recognition on video data. • Used CVAT and V7 Darwin for video label management. • Conducted quality assurance and peer reviews. • Created detailed annotation documentation to standardize workflow.

2023 - Present

AI Training Specialist / Data Annotation Specialist

LabelboxImageObject Detection

As an AI Training Specialist, I annotated image datasets for object detection, segmentation, and classification tasks. I ensured high-quality labels by using established frameworks and conducting quality assurance checks. I collaborated with machine learning engineers to improve labeling guidelines and workflow efficiency. • Applied accurate bounding boxes and polygons across diverse image datasets. • Maintained consistency and met production targets under tight deadlines. • Utilized tools such as Labelbox, CVAT, and Supervisely for annotation. • Routinely validated datasets using YOLO-based frameworks.

As an AI Training Specialist, I annotated image datasets for object detection, segmentation, and classification tasks. I ensured high-quality labels by using established frameworks and conducting quality assurance checks. I collaborated with machine learning engineers to improve labeling guidelines and workflow efficiency. • Applied accurate bounding boxes and polygons across diverse image datasets. • Maintained consistency and met production targets under tight deadlines. • Utilized tools such as Labelbox, CVAT, and Supervisely for annotation. • Routinely validated datasets using YOLO-based frameworks.

2023 - Present

Text

AppenTextPolyline

Worked on LLM training and evaluation projects focused on improving model accuracy, reasoning, safety, and response quality. Primary responsibilities included annotating and reviewing large-scale text datasets for Named Entity Recognition (NER), classification, question answering, summarization, and supervised fine-tuning (SFT). Created structured prompt-response pairs aligned with model training guidelines and performed RLHF-based evaluation by ranking model outputs based on relevance, coherence, factual accuracy, and safety compliance. Contributed to red teaming tasks by identifying edge cases, policy violations, hallucinations, and bias in generated outputs. Assisted in dataset cleaning, labeling consistency checks, and guideline refinement to improve annotation clarity and reduce inter-annotator disagreement. Worked on high-volume datasets exceeding thousands of samples per week while maintaining strict quality thresholds (95%+ accuracy targets). Followed multi-level QA review p

Worked on LLM training and evaluation projects focused on improving model accuracy, reasoning, safety, and response quality. Primary responsibilities included annotating and reviewing large-scale text datasets for Named Entity Recognition (NER), classification, question answering, summarization, and supervised fine-tuning (SFT). Created structured prompt-response pairs aligned with model training guidelines and performed RLHF-based evaluation by ranking model outputs based on relevance, coherence, factual accuracy, and safety compliance. Contributed to red teaming tasks by identifying edge cases, policy violations, hallucinations, and bias in generated outputs. Assisted in dataset cleaning, labeling consistency checks, and guideline refinement to improve annotation clarity and reduce inter-annotator disagreement. Worked on high-volume datasets exceeding thousands of samples per week while maintaining strict quality thresholds (95%+ accuracy targets). Followed multi-level QA review p

2025 - 2025

Education

Work History