Machine Learning Engineer
Current● Data Science: Participated in all stages of data analysis: discussing the task with partners, collecting primary data, generating additional data, selecting models,● Machine Learning Engineering: Executed model training (mostly LLMs. By various fine-tuning methods), constructed pipelines, and optimized model performance using various frameworks and techniques.● DevOps: Utilized Docker for containerizing applications.● Backend Engineering: Leveraged a variety of frameworks (such as FastAPI, Django, and Streamlit) for backend model implementation.