About the Role:
Wing is looking for a North American Logistics Systems Intern to join our Forward Logistics/ Global Transportation based in Palo Alto, CA.
The North American Logistics Systems Intern will design and develop next-generation logistics software solutions to support Wing’s rapid metro expansion across North America. In this role, you will build an integrated, AI-powered North American Transportation Management System (TMS) portal featuring automated inbound scheduling and a real-time operational metrics dashboard. By leveraging Google’s Gemini AI models alongside modern software development practices, you will transform logistics operations, streamline supply chain workflows, and enhance visibility across our distribution network.
In this role you will:
- Design, build, and deploy an integrated, AI-powered North American Transportation Management System (TMS) portal to optimize regional logistics workflows.
- Develop an automated inbound scheduling tool utilizing Google’s Gemini AI models to streamline dock operations and supply chain intake.
- Create a real-time operational metrics dashboard providing end-to-end visibility across Wing’s North American distribution network.
- Collaborate with cross-functional logistics and engineering teams to transform supply chain operations for rapid metro expansion.
- Build an AI-powered North American shipping portal to optimize logistics workflows and supplements TMS.
- Develop an automated inbound scheduling tool utilizing Google Gemini AI models for efficient dock operations.
- Create a real-time operational metrics dashboard providing full visibility across the distribution network.
What You’ll Need:
- Currently pursuing a Bachelor’s or Master’s degree in Supply Chain Management, Logistics, Industrial Engineering, Computer Science, or a related technical field, with an expected graduation date between December 2027 and August 2028.
- Demonstrated experience with software development and coding (e.g., Python, Java, or C++) applied to supply chain or logistics problems.
- Hands-on project experience or coursework involving AI/ML models (such as LLMs or Google Gemini) and data analytics for process optimization or dashboarding.
- Strong understanding of transportation management systems (TMS), inbound scheduling workflows, or distribution network logistics.
