AI Evaluation & Data Annotation Specialist | Vision, Video, LLM and QA
I am an AI evaluation and data annotation specialist with experience assessing image, video, audio, document, and LLM outputs for quality, accuracy, and guideline adherence. I evaluate AI-generated visuals for prompt adherence, rendering quality, temporal consistency, lighting, structure, and aesthetic flaws. I also create and review bounding boxes, semantic masks, object-tracking labels, descriptive tags, and multimodal QA datasets. My background in design systems and visual tools, including Adobe Photoshop, Illustrator, Figma, and CorelDRAW, enables me to provide detailed visual judgment and actionable feedback for computer vision and image-generation models. I have also audited speech transcriptions for phonetic accuracy, alignment, punctuation, and speaker diarization, and reviewed LLM responses for relevance, sentiment, quality, and rubric compliance. I am comfortable working with complex annotation guidelines, quality metrics, structured feedback workflows, and high-volume remote evaluation projects. I bring strong attention to detail, critical reasoning, consistency, and a practical understanding of how high-quality training data supports better AI systems.
AI Image & Video Evaluation Specialist at micro1 (2026 - Present) AI Trainer & Adobe Specialist at micro1 (2025 - 2026) Data Annotator & Multimodal QA Specialist at Turing / Moonvalley (2024 - 2026)
No QA report or evidence was submitted by the deadline, so there was no documented testing work to evaluate.