SwarmBench Task Engineer – Planning & Operations

About the role

Turing is seeking a SwarmBench Task Engineer to design and implement constraint‑driven benchmark tasks that simulate real‑world planning and logistics scenarios. You will work remotely on a short‑term contract, creating multi‑agent problems that help evaluate advanced AI models.

Key responsibilities

• Design planning and scheduling problems that reflect real‑world constraints such as logistics, capacity planning, and incident response.
• Model operational scenarios and create structured problem statements with dependencies and multiple variables.
• Develop Python scripts to assess feasibility, completeness, and optimality of benchmark tasks.
• Decompose complex tasks into sub‑problems suitable for multi‑agent systems.
• Collaborate with the team to improve task quality and evaluation standards.

Required profile

• 5+ years of experience in operations, project management, logistics, or supply‑chain management.
• Strong understanding of constraints, dependencies, and scheduling logic.
• Proven ability to work independently and meet deadlines on a remote basis.

Required skills

• Python programming.
• Optimization techniques such as linear programming, constraint satisfaction, and scheduling algorithms.

What we offer

• Short‑term contract (4 weeks) with a rate of $15 per hour.
• Fully remote work with flexible hours (20‑40 h/week) and required overlap with PST.
• Opportunity to contribute to cutting‑edge AI benchmarking projects.