Jameson Rich

Key Skills

Software

Appen

Clickworker

iMerit

Scale AI

Other

Top Subject Matter

Large Language Models (LLMs)

Rlhf Domain Expertise

AI benchmarking

Top Data Types

Video

Text

Image

Document

Top Label Types

Classification

Object Detection

Fine Tuning

Evaluation Rating

Data Collection

Question Answering

Text Generation

Transcription

Bounding Box

Polygon

Segmentation

Freelancer Overview

AI Model Evaluator / AI Trainer — Independent Contractor. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Diploma in Computer Science, Fitzwilliam Institute (2021) and Bachelor of Arts, United States International University – Africa (USIU-Africa) (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Model Evaluator / AI Trainer — Independent Contractor

Text

Evaluated large language model outputs for reasoning quality, factual accuracy, safety, and instruction compliance in support of RLHF and model fine-tuning. Conducted pairwise comparisons, preference ranking, and detailed rationales to guide AI improvement. Applied taxonomy-based annotation, detected hallucinations and inconsistencies, and authored structured explanations for use by model teams. • Evaluated GPT-4, Claude, Gemini outputs across multiple benchmarking criteria. • Produced structured rationales for model failures and annotated outputs using complex guidelines. • Conducted dataset quality assurance reviews and flagged annotation inconsistencies. • Supported RLHF and fine-tuning pipelines for commercial AI systems.

Evaluated large language model outputs for reasoning quality, factual accuracy, safety, and instruction compliance in support of RLHF and model fine-tuning. Conducted pairwise comparisons, preference ranking, and detailed rationales to guide AI improvement. Applied taxonomy-based annotation, detected hallucinations and inconsistencies, and authored structured explanations for use by model teams. • Evaluated GPT-4, Claude, Gemini outputs across multiple benchmarking criteria. • Produced structured rationales for model failures and annotated outputs using complex guidelines. • Conducted dataset quality assurance reviews and flagged annotation inconsistencies. • Supported RLHF and fine-tuning pipelines for commercial AI systems.

2023 - Present

AI Model Evaluator / AI Trainer — Independent Contractor

Scale AIImageBounding BoxPolygon

- Draw bounding boxes and polygons around objects in images to train object detection models. - Annotation of object instances with precise coordinates and class labels across large image datasets - Multi-class labeling on images with overlapping or occluded objects - Review and audit image classification batches for label consistency and accuracy - Annotate skeletal structures and joint positions across video frams for motion analysis datasets - Review images for labeling errors, guideline non-compliance and annotation inconsistencies.

- Draw bounding boxes and polygons around objects in images to train object detection models. - Annotation of object instances with precise coordinates and class labels across large image datasets - Multi-class labeling on images with overlapping or occluded objects - Review and audit image classification batches for label consistency and accuracy - Annotate skeletal structures and joint positions across video frams for motion analysis datasets - Review images for labeling errors, guideline non-compliance and annotation inconsistencies.

2023

AI Model Evaluator / AI Trainer — Independent Contractor

Scale AIVideoClassificationObject Detection

- Label objects across consecutive video frames using interpolation and tracking techniques - Annotate temporal events, actions and scene transitions in video datasets for activity recognition models

- Label objects across consecutive video frames using interpolation and tracking techniques - Annotate temporal events, actions and scene transitions in video datasets for activity recognition models

2023

Content Quality Analyst — Independent Contractor

OtherTextClassification

Reviewed and labeled high volumes of digital content for grammatical accuracy, tone, and contextual relevance according to editorial standards. Produced structured feedback and consistently documented actionable recommendations for improvement. Identified labeling inconsistencies and contributed to updated guidelines to enable reviewer alignment. • Labeled and classified digital written content according to complex editorial guidelines. • Authored structured feedback reports for systematic content evaluation. • Detected systemic errors and updated editorial annotation rules. • Supported quality assurance and consistency review processes.

Reviewed and labeled high volumes of digital content for grammatical accuracy, tone, and contextual relevance according to editorial standards. Produced structured feedback and consistently documented actionable recommendations for improvement. Identified labeling inconsistencies and contributed to updated guidelines to enable reviewer alignment. • Labeled and classified digital written content according to complex editorial guidelines. • Authored structured feedback reports for systematic content evaluation. • Detected systemic errors and updated editorial annotation rules. • Supported quality assurance and consistency review processes.

2021 - 2023

Content Quality Analyst — Independent Contractor

AppenTextClassificationQuestion Answering

Reviewed and annotated large batches of digital content for grammatical correctness, tonal consistency, relevance, and clarity according to strict editorial criteria. Generated structured feedback to identify and classify content quality issues for improved training datasets. Helped update annotation guidelines and contributed to reviewer alignment through identification of systemic inconsistencies. • Produced actionable content improvement reports • Ensured contextually relevant and error-free dataset text • Assisted with guideline refinements to improve labeling alignment • Classified and flagged ambiguous content for QA purposes

Reviewed and annotated large batches of digital content for grammatical correctness, tonal consistency, relevance, and clarity according to strict editorial criteria. Generated structured feedback to identify and classify content quality issues for improved training datasets. Helped update annotation guidelines and contributed to reviewer alignment through identification of systemic inconsistencies. • Produced actionable content improvement reports • Ensured contextually relevant and error-free dataset text • Assisted with guideline refinements to improve labeling alignment • Classified and flagged ambiguous content for QA purposes

2021 - 2023

Education

Work History