Joseph Murphy

Key Skills

Software

Appen

Remotasks

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Text

Video

Audio

Image

Top Label Types

Entity Ner Classification

Evaluation Rating

Object Detection

Prompt Response Writing SFT

RLHF

Text Generation

Transcription

Freelancer Overview

I am a dedicated professional with hands-on experience as an AI Trainer, where I have written high-quality prompts and carefully evaluated AI responses to ensure accuracy, safety, and clarity. My background in cybersecurity and ongoing studies in information technology have provided me with a strong understanding of data integrity and digital workflows. I am passionate about contributing to innovative AI projects, leveraging my skills in prompt engineering, data annotation, and critical analysis. My proven ability to deliver thorough justifications for findings, combined with my organizational and problem-solving skills, enables me to collaborate effectively within dynamic teams focused on AI and application development.

Labeling Experience

AI Trainer

Scale AIVideoEntity Ner Classification

In my role as a Video Data Annotator, I executed high-precision entity extraction and temporal labeling for computer vision training. I specialized in identifying and tracking specific objects, actions, and environmental features across various video datasets, utilizing bounding boxes, polygons, and keypoint movements to capture spatial-temporal data. To maintain model performance, I adhered to strict quality metrics, focusing on frame-by-frame consistency, accurate occlusion handling, and precise attribute tagging. This work ensured the development of robust visual perception systems, providing the high-fidelity labeled data necessary for the model to recognize and predict complex real-world interactions.

In my role as a Video Data Annotator, I executed high-precision entity extraction and temporal labeling for computer vision training. I specialized in identifying and tracking specific objects, actions, and environmental features across various video datasets, utilizing bounding boxes, polygons, and keypoint movements to capture spatial-temporal data. To maintain model performance, I adhered to strict quality metrics, focusing on frame-by-frame consistency, accurate occlusion handling, and precise attribute tagging. This work ensured the development of robust visual perception systems, providing the high-fidelity labeled data necessary for the model to recognize and predict complex real-world interactions.

2025 - 2025

AI Trainer

Scale AITextEvaluation Rating

In my role as an AI Content Evaluator on the Outlier platform, I spearheaded high-level Large Language Model (LLM) optimization through rigorous data labeling and comparative ranking tasks. I specialized in Reinforcement Learning from Human Feedback (RLHF), where I evaluated model outputs for factuality, logical coherence, and safety using complex multi-dimensional rubrics. My project portfolio included adversarial testing to identify edge-case vulnerabilities, hallucination mitigation through deep fact-checking, and the creation of ground-truth datasets for specialized domains. To ensure production-grade data quality, I maintained a high Quality Assurance (QA) success rate by providing granular, evidence-based justifications for every evaluation, directly contributing to the fine-tuning and alignment of next-generation AI systems.

In my role as an AI Content Evaluator on the Outlier platform, I spearheaded high-level Large Language Model (LLM) optimization through rigorous data labeling and comparative ranking tasks. I specialized in Reinforcement Learning from Human Feedback (RLHF), where I evaluated model outputs for factuality, logical coherence, and safety using complex multi-dimensional rubrics. My project portfolio included adversarial testing to identify edge-case vulnerabilities, hallucination mitigation through deep fact-checking, and the creation of ground-truth datasets for specialized domains. To ensure production-grade data quality, I maintained a high Quality Assurance (QA) success rate by providing granular, evidence-based justifications for every evaluation, directly contributing to the fine-tuning and alignment of next-generation AI systems.

2024 - 2025

AI Trainer

Scale AIImageEntity Ner ClassificationText Generation

In my work across multimodal datasets, I executed high-precision entity tagging and object detection tasks to train advanced computer vision and OCR models. This involved utilizing specialized tools to implement bounding boxes and semantic segmentation for complex image classification, ensuring every object was accurately localized and categorized. Simultaneously, I specialized in text generation projects where I authored high-quality synthetic data and descriptive captions to improve model understanding of visual context. To maintain a "Gold Standard" dataset, I adhered to strict quality measures—focusing on pixel-perfect accuracy, cross-referencing metadata for consistency, and performing rigorous error analysis to refine the model's predictive reliability.

In my work across multimodal datasets, I executed high-precision entity tagging and object detection tasks to train advanced computer vision and OCR models. This involved utilizing specialized tools to implement bounding boxes and semantic segmentation for complex image classification, ensuring every object was accurately localized and categorized. Simultaneously, I specialized in text generation projects where I authored high-quality synthetic data and descriptive captions to improve model understanding of visual context. To maintain a "Gold Standard" dataset, I adhered to strict quality measures—focusing on pixel-perfect accuracy, cross-referencing metadata for consistency, and performing rigorous error analysis to refine the model's predictive reliability.

2025

AI Trainer

Scale AIAudioEvaluation Rating

In my work with audio data, I performed high-fidelity comparative evaluations to optimize speech synthesis and recognition models. I conducted Side-by-Side (SbS) assessments of audio samples, ranking them based on auditory metrics such as naturalness, prosody, and phonetic clarity. My tasks included identifying artifacts like robotic distortion or unnatural clipping and labeling speech data for emotional tone and intent. By adhering to rigorous acoustic rubrics and inter-annotator consistency standards, I provided the nuanced feedback necessary to align AI-generated speech with human-like vocal patterns and regional accents.

In my work with audio data, I performed high-fidelity comparative evaluations to optimize speech synthesis and recognition models. I conducted Side-by-Side (SbS) assessments of audio samples, ranking them based on auditory metrics such as naturalness, prosody, and phonetic clarity. My tasks included identifying artifacts like robotic distortion or unnatural clipping and labeling speech data for emotional tone and intent. By adhering to rigorous acoustic rubrics and inter-annotator consistency standards, I provided the nuanced feedback necessary to align AI-generated speech with human-like vocal patterns and regional accents.

2025

Education

Work History