Freelancer Overview
I am a PhD-level AI Trainer and researcher with hands-on experience in designing. I have hands-on experience working on AI training and data labeling tasks, including image, video, and text-based annotations. My work has involved following detailed guidelines to ensure high-quality outputs, such as accurately labeling objects, actions, and scenarios, and validating data for consistency and correctness. I’m comfortable working with large volumes of data while maintaining attention to detail and meeting quality benchmarks.
I have also collaborated on projects that required real-world data collection, including mobile video recordings and task-based submissions. I’m familiar with quality review processes, feedback loops, and making quick corrections when needed. My strengths include clear guideline interpretation, consistency, time management, and delivering reliable training data that helps improve AI model performance., labeling, and evaluating high-quality training data for large language models, particularly in scientific and quantitative domains such as mathematics, physics, biology, and chemistry. My expertise lies in creating graduate-level problems, writing and validating robust Python solutions, and rigorously stress-testing AI outputs for logical consistency and accuracy. I am highly skilled in Python (NumPy, SciPy, Pandas, SymPy), data analysis, and model evaluation, and have contributed to the development and peer review of advanced LLMs by identifying reasoning flaws and enhancing model performance. My background in scientific research and technical documentation ensures a meticulous approach to data annotation and quality assurance, making me well-equipped to support AI and machine learning projects that require precise, domain-specific training data.
