• Design, train, and evaluate machine learning models across a range of research and applied AI initiatives • Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements • Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems • Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation • Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation • Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team • Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them • This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones