Andrew Tyerone Carter

Key Skills

Software

CVAT

Labelbox

Mercor

Snorkel AI

SuperAnnotate

Internal/Proprietary Tooling

Other

Top Subject Matter

Natural language processing

dataset quality

LLM outputs

Top Data Types

Audio

Computer Code Programming

Image

Text

Video

Document

Top Task Types

Audio Recording

Bounding Box

Computer Programming/Coding

Data Collection

Emotion Recognition

Entity (NER) Classification

Evaluation/Rating

Fine-tuning

Mapping

Object Detection

Polygon

Prompt + Response Writing (SFT)

Segmentation

Text Generation

Text Summarization

Transcription

Freelancer Overview

Remote AI Generalist (Freelance/Self Employed). Brings 4+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Labelbox, CVAT, and Other. Education includes High School Diploma, James Madison (2016). AI-training focus includes data types such as Text and Video and labeling workflows including Entity (NER) Classification, Transcription, and Evaluation.

Labeling Experience

AI Data Labeler – Video Annotation (Freelance/Self Employed)

CVATVideoTranscription

As part of multimedia dataset labeling, I generated captions and accurate timestamps for short-form videos, ensuring synchronization of audio and video content for model training purposes. This required describing visual and audio elements to improve video understanding for model development. I maintained high attention to detail to deliver precise and well-structured video labels. • Created captions reflecting content such as style, environment, music, and scene components. • Marked accurate timestamps for events, frame cuts, and object interactions within videos. • Ensured quality by synchronizing audio descriptions with visual data for AI model alignment. • Utilized both external and internal video labeling platforms including CVAT and SuperAnnotate.

As part of multimedia dataset labeling, I generated captions and accurate timestamps for short-form videos, ensuring synchronization of audio and video content for model training purposes. This required describing visual and audio elements to improve video understanding for model development. I maintained high attention to detail to deliver precise and well-structured video labels. • Created captions reflecting content such as style, environment, music, and scene components. • Marked accurate timestamps for events, frame cuts, and object interactions within videos. • Ensured quality by synchronizing audio descriptions with visual data for AI model alignment. • Utilized both external and internal video labeling platforms including CVAT and SuperAnnotate.

2023 - Present

Remote AI Generalist (Freelance/Self Employed)

LabelboxTextEntity Ner Classification

As a freelance AI generalist, I performed comprehensive annotation of text data, focusing on NLP and NER tasks using both internal and external labeling software. My responsibilities included labeling, transcription, prompt engineering, error analysis, and dataset curation to enhance LLM output and model training. I conducted transcription, quality assurance, and evaluation/rating to maintain high project standards and improve overall system performance. • Labeled, annotated, and curated text, audio, image, and video datasets using Labelbox, CVAT, SuperAnnotate, and internal proprietary tools. • Transcribed audio to text utilizing ICAO phonetic alphabet standards and performed POS tagging and coreference resolution. • Executed detailed quality assurance by analyzing data submissions and providing structured feedback for rework. • Designed and executed A/B testing for model evaluation and prompt engineering for large language models.

As a freelance AI generalist, I performed comprehensive annotation of text data, focusing on NLP and NER tasks using both internal and external labeling software. My responsibilities included labeling, transcription, prompt engineering, error analysis, and dataset curation to enhance LLM output and model training. I conducted transcription, quality assurance, and evaluation/rating to maintain high project standards and improve overall system performance. • Labeled, annotated, and curated text, audio, image, and video datasets using Labelbox, CVAT, SuperAnnotate, and internal proprietary tools. • Transcribed audio to text utilizing ICAO phonetic alphabet standards and performed POS tagging and coreference resolution. • Executed detailed quality assurance by analyzing data submissions and providing structured feedback for rework. • Designed and executed A/B testing for model evaluation and prompt engineering for large language models.

2023 - Present

Shannon 2

Internal Proprietary ToolingVideoPolygonEntity Ner Classification

label interpersonal affect evaluate the interpersonal effect based on the behavioral indicators and provide a label for the interpersonal effect train their system and improve the functions

label interpersonal affect evaluate the interpersonal effect based on the behavioral indicators and provide a label for the interpersonal effect train their system and improve the functions

2024 - 2024

Project Ribble - Driving and Intersection Complex Annotation US

Don T DiscloseImagePolygonText Generation

Review the annotations done during Part 1 (Simple Annotation) following the Part 1 Guidelines and Assign attributes. Part 2 (Complex Annotation) includes: Lane Attributes: Driving Lane priority ID and Exit Occlusion Metadata Attributes: Type of intersection and Type of action

Review the annotations done during Part 1 (Simple Annotation) following the Part 1 Guidelines and Assign attributes. Part 2 (Complex Annotation) includes: Lane Attributes: Driving Lane priority ID and Exit Occlusion Metadata Attributes: Type of intersection and Type of action

2024 - 2024

project Celandine EN QA

Snorkel AIAudioAudio Recording

QA Audio ensuring contributors adhere to the project guidelines and review the work of the contributors by listening to contributors audio recordings making notes of errors or guidelines that have not been adhered to and sending a detailed report back to the contributors on how to correct and adhere to the guidelines and rework the recordings.

QA Audio ensuring contributors adhere to the project guidelines and review the work of the contributors by listening to contributors audio recordings making notes of errors or guidelines that have not been adhered to and sending a detailed report back to the contributors on how to correct and adhere to the guidelines and rework the recordings.

2024 - 2024

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Education

Work History