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I have two distinct engagements with Mercor covering both ends of the AI training pipeline. As a Data Science Expert I designed adversarial evaluation frameworks to stress-test LLM reasoning for Gemini 2.5 Pro, engineering structured rubrics across 15+ datasets that intentionally surfaced systematic failure modes under multi-step reasoning and code generation tasks, maintaining a targeted 27% correctness rate under adversarial conditions. Prior to that I worked as a Short Video Captioning Expert where I was responsible for annotating short-form video content with high accuracy, capturing fine-grained visual and contextual details that passed through a rigorous three-stage review process. The acceptance rate under that review pipeline is a direct signal of annotation quality since each submission had to satisfy multiple independent reviewers before being accepted into the training dataset.
Yes, please mark that I have prior data labeling and AI training experience. I have worked with Mercor on two separate engagements covering both data annotation and AI model evaluation.
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Please add Mercor, Data Science Expert, August 2025 to September 2025, San Francisco, CA (Remote).
