Zoox - Machine Learning Engineer Intern, Simulation
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
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 or Seattle 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 • Fluency in C++ and/or Python, as well as a strong understanding of data structures and algorithms • Strong skills in mathematics, particularly linear algebra • Experience with large-scale code projects • Broad knowledge of Gaussian Splatting or Neural Radiance Fields • Strong understanding of generative AI techniques including diffusion, GAN, and transformers • Experience with game development or simulation frameworks used in robotics
Responsibilities
• Develop and implement machine learning models for simulation purposes within the company's projects. • Collaborate with team members to integrate AI solutions into existing workflows where applicable. • Analyze data sets relevant to current research initiatives in artificial intelligence, providing insights that can guide project direction. • Participate actively in meetings and contribute ideas for improving machine learning algorithms or processes within the company's projects. • Maintain a portfolio of work demonstrating proficiency with various AI tools commonly used by Zoox internationally, including but not limited to Python programming languages such as TensorFlow and PyTorch. • Engage in continuous professional development related to machine learning technologies through attending webinars, reading industry publications, or participating in relevant workshops/conferences when possible within the company's schedule constraints.
No credit card. Takes 10 seconds.