Boyd Jimmy

Key Skills

Software

Micro1

Mercor

Mindrift

Scale AI

Top Subject Matter

Video Annotation for AI Model Training

Video Annotation and Model Evaluation for AI

Text Data Annotation for AI

Top Data Types

Video

Text

Audio

Image

Document

Top Task Types

Classification

RLHF

Action Recognition

Bounding Box

Freelancer Overview

AI Data Annotator and Evaluator. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Micro1, Mercor, and Crossover. Education includes Bachelor of Science, University of Iowa (2018) and Postgraduate Professional Development Coursework, Illinois Institute of Technology (2022). AI-training focus includes data types such as Video, Text, and Audio and labeling workflows including Classification, RLHF, and Action Recognition.

Labeling Experience

AI Data Annotator and Evaluator

Micro1VideoClassification

Performed structured annotation and output quality review for AI model improvement workflows. Consistently maintained accuracy standards while handling large volumes of annotation tasks across varied project categories. Applied rigorous evaluation criteria to diverse task batches, adapting to updated labeling protocols efficiently. • Conducted video annotation tasks focused on model refinement • Assessed and reviewed AI output for accuracy benchmarks • Managed asynchronous high-volume annotation projects • Adapted rapidly to evolving platform guidelines

Performed structured annotation and output quality review for AI model improvement workflows. Consistently maintained accuracy standards while handling large volumes of annotation tasks across varied project categories. Applied rigorous evaluation criteria to diverse task batches, adapting to updated labeling protocols efficiently. • Conducted video annotation tasks focused on model refinement • Assessed and reviewed AI output for accuracy benchmarks • Managed asynchronous high-volume annotation projects • Adapted rapidly to evolving platform guidelines

2025 - Present

AI Data Annotator and Model Evaluator

MercorVideoClassification

Delivered precise video annotation following structured protocols for AI training pipelines. Managed advanced and confidential labeling tasks requiring strict adherence to data handling standards. Provided comparative model evaluation contributing to quality assurance across multiple project tracks. • Implemented structured video labeling on extended batches • Supported advanced AI research annotation projects • Delivered calibrated, multi-track model evaluations • Maintained quality under strict guidelines

Delivered precise video annotation following structured protocols for AI training pipelines. Managed advanced and confidential labeling tasks requiring strict adherence to data handling standards. Provided comparative model evaluation contributing to quality assurance across multiple project tracks. • Implemented structured video labeling on extended batches • Supported advanced AI research annotation projects • Delivered calibrated, multi-track model evaluations • Maintained quality under strict guidelines

2024 - Present

AI Data Annotator and RLHF Evaluator

TextRLHF

Conducted RLHF ranking and evaluation on AI-generated responses using formal rubrics and detailed justifications. Labeled image generation outputs for accuracy, prompt matching, and precision across diverse categories. Executed Python-based annotation scripting for structured data production on platform-specific tasks. • Performed pairwise comparison tasks on AI responses • Annotated large batch image generation samples • Implemented Python scripts for data validation and formatting • Worked across structured text and image labeling tasks

Conducted RLHF ranking and evaluation on AI-generated responses using formal rubrics and detailed justifications. Labeled image generation outputs for accuracy, prompt matching, and precision across diverse categories. Executed Python-based annotation scripting for structured data production on platform-specific tasks. • Performed pairwise comparison tasks on AI responses • Annotated large batch image generation samples • Implemented Python scripts for data validation and formatting • Worked across structured text and image labeling tasks

2024 - 2024

Voice and Audio Data Annotator

AudioClassification

Delivered comprehensive audio and voice annotation, including speaker identification and transcription quality review. Labeled acoustic events in large batches, meeting accuracy and turnaround standards of enterprise speech AI projects. Maintained strict compliance with detailed annotation guidelines for precise segmentation and data formatting. • Labeled speaker and acoustic event data in audio files • Reviewed and classified transcription quality • Ensured detailed segmentation and sound classification • Met enterprise-grade turnaround requirements

Delivered comprehensive audio and voice annotation, including speaker identification and transcription quality review. Labeled acoustic events in large batches, meeting accuracy and turnaround standards of enterprise speech AI projects. Maintained strict compliance with detailed annotation guidelines for precise segmentation and data formatting. • Labeled speaker and acoustic event data in audio files • Reviewed and classified transcription quality • Ensured detailed segmentation and sound classification • Met enterprise-grade turnaround requirements

2024 - 2024

AI Data Labeller and Quality Reviewer

TextClassification

Completed classification-based text data annotation within a high-throughput, remote environment. Sustained rigorous platform quality and accuracy thresholds throughout engagement. Efficiently adapted to detailed workflow changes while ensuring high data submission throughput. • Performed structured text annotation and labeling • Upheld quality standards in performance-monitored workflows • Adapted dynamically to evolving task guidelines • Ensured reliability and accuracy on varied data sets

Completed classification-based text data annotation within a high-throughput, remote environment. Sustained rigorous platform quality and accuracy thresholds throughout engagement. Efficiently adapted to detailed workflow changes while ensuring high data submission throughput. • Performed structured text annotation and labeling • Upheld quality standards in performance-monitored workflows • Adapted dynamically to evolving task guidelines • Ensured reliability and accuracy on varied data sets

2024 - 2024

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Education

Work History