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Mercor
Mindrift
OneForma
Telus
Appen
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Text
Audio
Evaluation/Rating
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Data Collection
ClassificationI have experience contributing to AI training and evaluation projects involving conversational AI, Large Language Models (LLMs), audio systems, and multimodal AI applications. My work includes evaluating AI-generated responses for accuracy, relevance, coherence, safety, and instruction-following, as well as identifying hallucinations, biases, and edge-case failures. I have also performed audio testing by validating speech-to-text outputs and assessing voice interactions, alongside visual testing of AI systems that process image-based inputs. Through structured feedback, annotation, and quality scoring, I have helped improve model performance and user experience. In addition to AI-focused work, I bring over three years of software testing experience, which strengthens my ability to detect defects, analyze patterns, and maintain high-quality standards. My background includes test case design, bug reporting, functional testing, API validation, and data analysis. What sets me apart is my combination of analytical thinking, attention to detail, strong communication skills, and a deep understanding of how humans interact with AI systems. This enables me to provide high-quality training data, accurate annotations, and actionable feedback that supports the development of more reliable and effective AI models.
AudioTranscriptionValidated speech-to-text outputs by reviewing transcription accuracy, speaker recognition, punctuation, and contextual understanding. Identified recognition errors, accent-related issues, and language inconsistencies to improve ASR (Automatic Speech Recognition) models and voice-enabled AI systems.
TextEvaluation/RatingEvaluated and annotated AI-generated responses to improve the performance, accuracy, and safety of Large Language Models (LLMs). Assessed outputs for instruction adherence, factual accuracy, relevance, coherence, tone, and overall response quality. Identified hallucinations, biases, harmful content, and logical inconsistencies while providing detailed feedback to support model refinement and reinforcement learning from human feedback (RLHF) workflows. Conducted prompt-response testing across diverse domains, including business, education, customer support, and general knowledge. Created quality ratings, compared model outputs, documented edge cases, and contributed to training datasets used for model improvement. Leveraged strong analytical and quality assurance skills to ensure high-quality annotations and reliable AI performance in real-world conversational scenarios.
Bachelors, Engineering
Master Data Lead
Data Analytics Tutor
