Zoox - Machine Learning Engineer Intern, Autonomy Behavior
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Requirements
• Currently working towards a B.S., M.S., Ph.D., or advanced degree in a relevant engineering program • Must be returning to school to continue your education upon completing this internship • Good academic standing • Able to commit to a 12-week internship beginning in May or June of 2026. • At least one previous industry internship, co-op, or project completed in a relevant area • Ability to relocate to the Bay Area, California for the duration of the internship • Interns at Zoox may not use any proprietary information they are working on as part of their thesis, any published work with their university, or to be distributed to anyone outside of Zoox • Advanced understanding of Python or C++ • Strong experience with PyTorch and/or JAX • Experience with production ML pipelines: dataset creation, labeling, training, metrics • Experience with Neural Network design and implementation • Strong track record in machine learning for autonomous driving, robotics, or LLMs • Publication at top-tier conferences (e.g., NeurIPS, ICML, CoRL, CVPR, ICCV, ECCV, IROS, ...) • Familiarity with applying ML visualization and introspection techniques
Responsibilities
• Develop and implement machine learning models to improve the efficiency of autonomous vehicle navigation systems. • Collaborate with cross-functional teams to integrate AI solutions into existing workflows within Zoox's Autonomy Behavior project. • Conduct experiments, analyze results, and iterate on model designs based on performance metrics relevant to safety and reliability in autonomous driving scenarios. • Contribute code reviews for peer programming sessions focused on maintaining high coding standards across the team’s projects. • Stay updated with industry trends and emerging technologies related to machine learning applications in transportation, attending workshops or webinars as necessary.