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Symbotic is offering a Summer Intern - Machine Learning Ops to join the ML Operations team within the Software organization. You will help build, scale, and deploy machine learning systems that improve health, reliability, and performance of our autonomous warehouse robot fleet.
You will collaborate across ML research, software, hardware, and operations to scale monitoring and deployment infrastructure. The internship emphasizes mentorship, professional development, and exposure to end-to-end
Time type: full time
Posted on: October 08, 2026
Job requisition id: R8202
Term: Summer (May-Aug)
At Symbotic, early career talent plays a meaningful role in helping us reimagine the future of supply chain automation. Through our Internship and Co-op programs, students have the opportunity to contribute to real projects, collaborate with experienced engineers and business leaders, and gain hands‑on exposure to the technologies powering our end‑to‑end robotics and automation solutions. We are looking for curious, motivated students who are excited to solve complex problems, bring new perspectives to cross‑functional teams, and see their work make an impact in a fast‑moving, innovative environment.
Along the way, Interns and Co‑ops are supported through mentorship, professional development, networking opportunities, and a robust calendar of events designed to help them build community and grow their careers. Symbotic offers transportation and housing benefits for students who meet our relocation requirements.
Continue reading below to learn more about this exciting opportunity!
Symbotic is seeking for an Intern- Machine Learning Ops to join our ML Operations team within our Software organization. Your job will be to help build, scale, and deploy machine learning systems that improve the health, reliability, and performance of our autonomous robot fleet.
The ML Operations team takes machine learning and perception technologies from research environments into reliable production use across Symbotic's autonomous warehouse robots. The team partners with machine learning research, software, hardware, perception, and operations groups to scale predictive monitoring, computer vision, deployment infrastructure, and robotic health monitoring capabilities.