Helen Badmus

Transcribes and validates speech/audio clips for AI data workflows, with 5,000+ clips completed. Checks recordings and transcripts for accuracy, completeness, consistency, and compliance with project guidelines.

Builds and tests responsive interfaces for AI-related tools using HTML, CSS, and JavaScript. Reviews AI-generated outputs for accuracy, relevance, instruction following, consistency, and alignment with user intent.

Evaluated LLM responses for factual accuracy, relevance, safety, and adherence to evaluation guidelines. Applied rubrics to assess prompt-response pairs and multi-turn conversations for instruction following and context awareness.

Organized digital assets, content calendars, spreadsheets, and recurring administrative workflows. Maintained accurate records and coordinated information to support remote operations.

Captured and submitted video and audio datasets for computer-vision and audio machine-learning projects. Followed collection and quality-control instructions and reviewed submissions for accuracy and completeness.

Evaluated multi-turn conversations and AI-generated responses for factual correctness, coherence, relevance, and natural-language quality. Completed annotation, ranking, and RLHF tasks using project-specific quality standards.

Recorded, reviewed, and validated speech and audio samples for speech-recognition and text-to-speech workflows. Followed data-quality requirements and checked samples for consistency, completeness, and compliance.

Performed exploratory, functional, and regression testing on mobile and web applications. Reported defects with reproducible steps, screenshots, and supporting evidence.

Completed the AI Fluency: Framework and Foundations certification in 2026.

Completed the Microsoft Azure AI Essentials: Workloads and Machine Learning on Azure certification in August 2026.

Completed a Bachelor of Science in Computer and Data Science in November 2023.