We are seeking a Machine Learning Researcher to contribute to research on interpretable AI methods for learning-based automated driving systems. This role is ideal for a researcher who enjoys hands-on experimentation, model development, and evaluation, and who wants to work on foundational problems at the intersection of autonomy, interpretability, and safety. You will work closely with senior researchers and engineers to develop methods that make end-to-end neural driving policies more interpretable, diagnosable, and verifiable, while preserving performance and scalability. Your work will contribute to building “glass-box” representations that help engineers and researchers better understand, debug, and validate learned driving behaviors.