The work spans a broad range of modeling techniques—from XGBoost models used in financial risk scoring, to transformer-based architectures for personalization, and LLM-powered components integrated into user-facing systems. However, this is not a dedicated LLM fine-tuning role—while experience with LLMs is valued, this role requires practical experience in applying a variety of ML approaches to real-world problems at scale.