AI Engineer with hands-on experience building LLM-powered applications, including RAG pipelines, conversational agents, and NLP systems. Skilled in Python, Hugging Face, and PyTorch, with a focus on developing practical, production-ready AI solutions. Strong interest in model optimization, scalable deployment, and real-world AI applications.
AI Engineer with hands-on experience building LLM-powered applications, including RAG pipelines, conversational agents, and NLP systems. Skilled in Python, Hugging Face, and PyTorch, with a focus on developing practical, production-ready AI solutions. Strong interest in model optimization, scalable deployment, and real-world AI applications.
• Built an image classification system using Python and Scikit-learn to perform automated testing and technical validation of diagnostic attributes. • Implemented extensible data processing frameworks using NumPy and Pandas to optimize the handling of complex datasets for software enhancements. • Tested design hypotheses in simulated environments to identify logic defects, resulting in more reliable and diagnosable identification patterns. • Documented software architecture and project outcomes to ensure the solution is maintainable and ready for future deployment and maintenance.
• Developed an automated engine using Python to facilitate structured evaluations based on predefined technical criteria and real-time responses. • Designed state management flows to ensure consistent data context during interactions, improving the reliability and diagnosability of the software system. • Created objective evaluation frameworks to identify software improvement opportunities through data-driven performance analysis and SQL reporting. • Utilized Jupyter Notebook for exploratory analysis to refine software components and test technical hypotheses under technical leadership.