About this role
Join a groundbreaking initiative to develop realistic enterprise environments for training and evaluating frontier AI agents. As a chemical engineering expert, you will leverage your experience from leading chemical, petrochemical, and specialty-materials companies to recreate digital workspaces that reflect real-world operations. Your expertise will be pivotal in designing tasks that challenge cutting-edge AI systems.
Key Responsibilities- Construct a realistic digital workspace that includes essential documents such as process flow diagrams, P&IDs, PHA/HAZOP reports, mass and energy balance models, turnaround plans, OSHA PSM documentation, and relevant email threads.
- Create multi-step tasks based on actual workflows that require navigating various applications, files, and stakeholders, effectively challenging frontier AI agents.
- Collaborate with fellow chemical-engineering professionals to design the environment, define task scope, and review scenarios for realism and rigor.
- Work asynchronously with research teams to refine task designs and evaluation criteria for chemical-process agent benchmarks.
- Contribute to frontier AI research and benchmarking, directly influencing how leading labs train and evaluate the next generation of AI systems.
- BS, MS, or PhD in Chemical Engineering or a related discipline.
- 3+ years of full-time experience at a Fortune 500 chemical, petrochemical, or specialty-materials company, or a major engineering/EPC firm.
- Experience in one or more of the following areas:
- Process design, simulation, or scale-up.
- Plant operations, operations engineering, or turnaround planning.
- Process safety (PHA/HAZOP, PSM under 29 CFR 1910.119).
- R&D or product development.
- EH&S, emissions compliance, or sustainability engineering.
- PE license is a plus.
- Proficient in using CHEMKIN, Aspen Plus, ANSYS Fluent, STAR-CCM+, and Siemens Opcenter or Rockwell FactoryTalk.
- Strong analytical thinking and writing skills, with the ability to translate process-industry workflows into structured task specifications.
This project will initially offer an effective hourly rate, transitioning to a compensation model based on the throughput of quality work.
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