Seeking motivated software interns passionate about ML systems and MLOps to contribute to autonomous driving infrastructure projects. The role involves analyzing performance bottlenecks, enhancing observability, developing MLOps tools, and processing large-scale human driving and physiological data. Interns will collaborate with senior engineers, improve ML pipelines, and support research on human-vehicle interactions. Qualifications include proficiency in Python, ML frameworks like PyTorch, containerization, scalable workflows, and version control. Preferred skills include distributed training, cloud infrastructure, and experience with perception systems. This position offers hands-on experience in production-grade ML infrastructure, impacting safety-critical autonomous driving solutions, with opportunities for technical growth and contribution to core platform development.