About this role
This position offers a unique opportunity to leverage your expertise in supply chain and logistics within an innovative project aimed at enhancing AI capabilities. You will collaborate with leading AI labs on an initiative to create realistic enterprise environments where AI agents can be trained and evaluated. Your role will involve recreating the digital workspaces of Fortune 500 companies and designing tasks that challenge cutting-edge AI technologies.
Key Responsibilities- Develop a realistic digital workspace using the tools and files you utilize daily, including S&OP decks, network-design models, carrier RFPs, inventory reports, and performance dashboards, while incorporating relevant platforms such as Manhattan Associates WMS or SAP S/4HANA.
- Create multi-step tasks that reflect your real workflows, requiring interaction with various applications, files, and stakeholders to effectively challenge advanced AI agents.
- Collaborate with fellow supply chain and logistics professionals to design the environment, define task scope, and review scenarios for accuracy and rigor.
- Engage asynchronously with research teams to refine task designs and evaluation criteria for supply chain agent benchmarks.
- Contribute to pioneering AI research and benchmarking, with your work directly influencing how leading labs train and evaluate future AI systems.
- Minimum of 3 years of full-time experience in a Fortune 500 retailer, manufacturer, 3PL, or large carrier.
- Experience in areas such as:
- Demand/supply planning and S&OP/IBP
- Transportation management, carrier sourcing, or network design
- Warehouse operations, DC management, or WMS/labor planning
- Procurement/sourcing/supplier management
- Global trade, customs, or international logistics
- Certifications such as APICS CPIM, CSCP, or CLTD are a plus.
- Proficient in using tools like Manhattan Associates WMS, Blue Yonder, SAP S/4HANA, and Tableau/Power BI.
- Strong analytical and writing skills, with the ability to translate supply chain workflows into structured task specifications.
This project will initially operate on an hourly rate, transitioning to a compensation model based on the throughput of quality work.
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