Birmingham City University
Master in Computer Science, Computer Science
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I have experience with AI training and data labelling because I worked with Outlier to make the outputs of large language models better by evaluating, annotating, and improving training data. My job was to check AI-generated answers for accuracy, coherence, and alignment with user intent, as well as give structured feedback to help the model work better. I did a lot of different things, like evaluating prompts, ranking responses, finding errors, and rewriting outputs to make sure they met quality and safety standards. This needed a lot of focus on the details, the ability to think critically, and the ability to consistently understand complex rules. Along with execution, I came up with a methodical way to make sure of quality by making sure that annotations were consistent and outputs matched expected behaviours. My background as a principal frontend engineer further strengthens my contribution, as I bring a deep understanding of how AI systems integrate into real-world applications, particularly in user-facing products. This allows me to evaluate outputs not just for correctness but for usability, clarity, and practical relevance. I am comfortable working with evolving guidelines, handling ambiguity, and maintaining high throughput without compromising quality, making me well-suited for scalable AI training and data curation efforts.
Master in Computer Science, Computer Science