Operations Expert with Python for AI Supply Chain Task Design

Toptal | Anywhere in the World

Ónyénwē Oge zuru ezu Data Science na analytical
Na-egosi ndesịta nke mbụ (English) Gosi ntụgharị
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Overview
A fast-growing AI data company is hiring supply chain practitioners to design expert-level Terminal-Bench tasks for evaluating AI agents. You will turn real planning work into end-to-end challenges, each with files, a working solution and an automated correctness check. The goal is to build a benchmark grounded in real operations work.
***THIS IS A TASK BASED COMPENSATION MODEL. PLEASE CHECK THE APPLICATION QUESTIONS FOR MORE DETAILS.***
Responsibilities
• Design expert-level Terminal-Bench tasks by turning a real supply chain task from your work into a challenge an AI agent solves end to end.
• Define the files, data exports and systems each task runs on, such as ERP, MES and WMS extracts, so the scenario reflects realistic planning conditions.
• Write a working solution for each task, for example a 5-day production plan, and confirm it can be solved in 60 to 75 minutes.
• Build the automated check that proves the result is correct, using tests or scripts that accept valid answers and catch planning errors objectively.
• Document the written rules, constraints and SOPs that decide each case, along with realistic edge cases, data inconsistencies and common planner errors from your process.
• Iterate on tasks based on reviewer feedback, keeping instructions unambiguous, data consistent and the solution and verification reproducible in a command-line environment.
Skills/Experience
• 3+ years of hands-on supply chain or production planning work (not only studying, selling or managing it), or a PhD with active research in the subfield
• Did the work within the last 3 years and can name the systems, tools, data and rules used
• Personally executed a process where each case is decided by written rules such as SOPs, planning rules or constraints
• Worked inside systems of record (ERP, WMS) and with their exports or reports
• Can describe edge cases, data inconsistencies and common planner errors, and how a mistake would be caught
• Technical fluency in Python or another language and the command line, plus files, CSV/JSON, APIs or databases
• Available to start around November 4, 2026
Nice-to-have
• Automated or audited the process with scripts, SQL, RPA or rules engines
• 5+ years in the same process family
• Docker, Git and experience writing tests
• Hands-on experience with SAP or other ERPs and TMS/WMS platforms
• Advanced Excel skills
Process
• Task-based engagement paid per task, with each task taking about 60 to 75 minutes
• Vetting task instead of a live interview
• Tasks are reviewed by the client before approval

This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.

Nhazi

Docker, Git, Inventory Management, Supply Chain, Microsoft Excel, Python, SAP, SAP Production Planning, SQL, Supply Chain Operations

Ndesịta ozi ndị ahụ

Nhazi: 0 afọ

Ékètara: 2 hours, 17 minutes gara aga

Nlebiritụanya: 5

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