Operations Analyst | $15.3/hr Remote

Position: SwarmBench Task Engineer Planning / Operations Type: Contractor (Short-term 4 weeks) Compensation: $15/hour Location: Remote Commitment: 20-40 hours/week (with 4 hours overlap with PST) Role Responsibilities Design and develop multi-agent benchmark tasks involving planning, scheduling, and resource allocation. Create real-world operational scenarios (logistics, project management, incident response, capacity planning) Build constraint-rich problem statements with multiple dependencies and variables Develop Python-based scripts to evaluate feasibility, completeness, and optimality Break down complex problems into structured sub-tasks for multi-agent systems Model scenarios with timelines, dependencies, and resource constraints Collaborate with teams to improve task quality, coverage, and evaluation rigor Requirements Strong experience in operations, project management, logistics, or supply chain Strong understanding of constraints, dependencies, and scheduling logic Proficiency in Python for validation and verification scripting Strong structured problem-solving and decomposition skills Ability to model real-world operational scenarios Clear technical communication and documentation skills Ability to work in a fast-paced environment and meet deadlines Preferred Qualifications Experience with optimization techniques (linear programming, constraint satisfaction, scheduling algorithms) Background in operations research Experience with simulation or modeling tools Familiarity with AI planning systems or automated reasoning Experience with AI benchmarks (e.g., SWE-bench, Terminal-bench) Hands-on experience with Docker Application Process Apply via Easy Apply Receive Role Details & Google Form via Email Shortlisted Candidates Receive Interest Check Form (ICF) Complete the Interest Check Form, Online Assessment & Take-Home Assessment Final Selection & Onboarding Position: SwarmBench Task Engineer Planning / Operations Type: Contractor (Short-term 4 weeks) Compensation: $15/hour Location: Remote Commitment: 20-40 hours/week (with 4 hours overlap with PST) Role Responsibilities Design and develop multi-agent benchmark tasks involving planning, scheduling, and resource allocation. Create real-world operational scenarios (logistics, project management, incident response, capacity planning) Build constraint-rich problem statements with multiple dependencies and variables Develop Python-based scripts to evaluate feasibility, completeness, and optimality Break down complex problems into structured sub-tasks for multi-agent systems Model scenarios with timelines, dependencies, and resource constraints Collaborate with teams to improve task quality, coverage, and evaluation rigor Requirements Strong experience in operations, project management, logistics, or supply chain Strong understanding of constraints, dependencies, and scheduling logic Proficiency in Python for validation and verification scripting Strong structured problem-solving and decomposition skills Ability to model real-world operational scenarios Clear technical communication and documentation skills Ability to work in a fast-paced environment and meet deadlines Preferred Qualifications Experience with optimization techniques (linear programming, constraint satisfaction, scheduling algorithms) Background in operations research Experience with simulation or modeling tools Familiarity with AI planning systems or automated reasoning Experience with AI benchmarks (e.g., SWE-bench, Terminal-bench) Hands-on experience with Docker Application Process Apply via Easy Apply Receive Role Details & Google Form via Email Shortlisted Candidates Receive Interest Check Form (ICF) Complete the Interest Check Form, Online Assessment & Take-Home Assessment Final Selection & Onboarding