US-Based Remote AI Annotation Specialist, Data Labeling Expert, Team Lead, QA Moderator, Reviewer, and AI Trainer.
Available for immediate remote contract work. I have moderated teams, directed training conferences, monitored performance metrics, and maintained inter‑transcriber or annotator reliability across large‑scale projects. I prioritize communication and advanced functionality for high‑precision data labeling and effective team management. Highly experienced in large-scale Video-Language Model (VLM) training, bounding box generation, 360° video labeling, Natural Language Processing (NLP) data analysis, audio transcription, and high-precision image annotation for generative AI model tasks.
My professional background includes processing thousands of high-precision AI annotations across diverse datasets. I possess a highly refined capacity for advanced pattern recognition, anomaly detection, verifying phonetic accuracy against somatic intent, and auditing data integrity. By anticipating friction points in complex RLHF (Reinforcement Learning from Human Feedback) workflows, I systematically catch critical edge cases, data corruptions, and semantic ambiguities that standard evaluation processes miss.
Availability
Part time or Full time (preferably 40+ hours). 20 to 80 hours weekly for 1 to 6+ month projects.
Task Completion Rate
600 easy (1 minute each) tasks in approximately 8 hours. 60 complex (8+ minutes each) tasks done in approximately 8 hours.
Annotation Components
Instruction Following
Prompted objects, subjects, environments, sounds, and actions must all be provided.
Visual Issues
Compressed texture
Flickering texture effect
Gradient banding
Framerate abnormalities
Blur
Overexposed lighting
Zoom
Camera framing
Scene cuts
Color saturation
Color saturation
Phonetic glitching
AI Generated
Morphed objects and anatomy
Extra limbs
Actions defying gravity
Unnatural textures
Unnatural lighting that doesn’t coincide with the environment
Unnatural or incorrect anatomy
Phasing through objects, subjects, or the environment
Audio Issues
Diarization correctness
Unsynchronized voice to mouth
Mispronunciation
Disrupted speech and audio
Synthetic voice effect
Pacing
False start
Digital artifacts (garbled speech, metallic tone, wobbling pitch, pops, clicks,
Compressed audio
Missing audio
Audio stuttering
Incorrect sounds
Team Leadership & Moderation
I have worked as a remote Team Lead and QA Moderator for AI training projects, overseeing teams of transcriptionists, annotators, and reviewers.
Experience:
Directing training conferences and providing group or individual guidance to improve comprehension of project guidelines.
Monitoring individual and team performance metrics, delivering weekly feedback, and maintaining consistent output quality.
Resolving transcription disputes and maintaining high inter‑transcriber or annotation expert reliability for teams.
Coordinating with project managers to assess team capacity, adjust production targets, and resolve workflow challenges.
Determining issues to escalate for complex audio files, providing accurate resolution and quality assurance.
Video-Language Model (VLM) Annotation & Bounding Box Projects
Human Recorded Video Data QA Validation
Verified bounding boxes and masks for video content, ensuring spatial accuracy and model alignment. Conducted thorough Quality Assurance (QA) and factual data integrity validation of AI-generated annotations, identifying edge cases and functional conflict potential.
360° Video Generative AI Annotation
Worked as a Reviewer AI Trainer, annotating and reviewing 360° video data for AI training models. Focused on complex object tracking, anomaly detection, and scene understanding. Processed thousands of frames utilizing precise bounding box and masking techniques.
Audio Annotation, NLP Data Analysis & Transcription
Transcribed thousands of English audio files featuring complex East Asian voice accents using Labelbox. Applied NLP (Natural Language Processing) evaluation to verify phonemes against semantic intent, minimizing errors caused by conversational ambiguity and improving language app datasets.
Audio Recording & TTS Generative AI Training
Created high-quality audio recordings for AI-generated Text-to-Speech (TTS) scripts. Evaluated the accuracy of AI-generated data by comparing it against factual sources, and rated other users’ audio prompts for quality, somatic intent, and output consistency.
LLM Prompt Engineering & Image Data Labeling
Human Created & AI-Generated Media Annotation
Performed advanced data annotation and RLHF tasks for human and AI-generated media using Airtable, Parimango, Multimango, and Facebook’s internal annotation platform. Completed thousands of image annotation tasks to improve LLM and generative AI processing, clarity, and output effectiveness.
Project Leadership, Auditing & Process Improvement
I have strategically analyzed and restructured project guidelines for high‑value video and audio annotation initiatives, improving navigational interfaces and data formats to optimize user comprehension, mitigate instructional ambiguity, and greatly increase output efficiency.
Accomplishments:
Worked as a Reviewer for 1 Alignerr AI training audio project, 3 micro1 AI video annotation projects, 1 micro1 audio tagging project, and 1 Turing transcription AI training project.
Provided strict data integrity, factual correctness, and QA standards for all deliverables.
Created detailed, actionable feedback to optimize the future performance of annotation experts.
Identified and resolved edge cases, data corruptions, and ambiguities that normal observational processes fail to evaluate.
Moderated and trained transcriptionists on complex accent audio projects, improving comprehension of guidelines and reducing error rates.
Ashley Rogers 