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TextI bring over five years of hands-on experience in AI engineering and software development, with a strong focus on data labeling, annotation, and quality assurance for NLP and large language models. My background includes evaluating and improving AI-generated outputs for accuracy, bias, and guideline compliance, as well as designing review templates and rubrics to streamline annotation processes. I have worked extensively with Python, deep learning frameworks like TensorFlow and PyTorch, and have conducted research and development in areas such as text classification, sentiment analysis, and prompt engineering. My experience spans both enterprise and freelance projects, where I have audited AI datasets, mentored teams on evaluation best practices, and contributed to building reliable, ethical AI systems. I am passionate about ensuring high-quality training data and model outputs, and thrive in environments focused on responsible AI development.
Evaluated AI-generated solutions for programming, logical reasoning, and algorithmic problem-solving tasks.
Worked on large-scale data annotation and evaluation projects aimed at improving the performance, safety, and alignment of Large Language Models (LLMs). Responsibilities included reviewing, rating, and refining AI-generated text to support supervised fine-tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) pipelines.
Master of Technology, Computer Science
Bachelor of Technology, Computer Science
Senior Software Developer / AI Engineer
Software Developer
