Type: Contract
Location: Remote
Interview language: English
If you are a chemical engineer who thrives on technical precision, applied problem-solving, and real-world process reasoning, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex chemical engineering concepts. We are looking for chemical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Chemical Engineer will directly help improve the world’s premier AI models, and will play an important role in shaping the future of AI. This role is a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs.
4+ years of professional chemical engineering experience, with meaningful hands‑on work in process design, plant/operations engineering, process safety, scale‑up, manufacturing, utilities, EHS, quality, R&D, controls/automation interfaces, or a closely related chemical engineering specialty.
Deep knowledge of chemical engineering fundamentals, including material & energy balances, thermodynamics, fluid mechanics, heat & mass transfer, reaction engineering, separations (distillation, absorption, extraction, membranes), unit operations, and process control concepts.
Strong comfort with engineering calculations, assumptions, constraints, and defensible reasoning (including uncertainty, safety factors, and limitations).
Bachelor’s degree in Chemical Engineering (or closely related) required; Master’s/PhD, PE/Chartered credentials, or advanced professional certifications strongly preferred.
Previous experience with AI data training, annotation, red‑teaming, or evaluating AI-generated technical content is a strong plus.
Familiarity with tools and artifacts such as PFDs/P&IDs, Aspen Plus/HYSYS, CHEMCAD, process datasheets, PSM documentation, HAZOP/LOPA, or SOPs is a plus.
Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across chemical engineering topics.
Challenge advanced language models with realistic chemical engineering scenarios, calculations, and process‑informed reasoning tasks.
Review and refine AI-generated prompts, model responses, explanations, and step‑by‑step engineering solutions.
Provide structured feedback that identifies factual errors, flawed assumptions, missing constraints, unsafe recommendations, unit/consistency mistakes, or incomplete reasoning.
Assess model performance on topics such as: Material & energy balances, phase behavior, and thermodynamic property use, Unit operations and sizing logic, Distillation/separations design logic and feasibility checks, Process control reasoning, Process safety, Scale‑up/manufacturability, operability, and troubleshooting of plant scenarios
Help shape AI communication standards for technical chemical engineering content, including how models explain assumptions, limitations, calculations, and professional judgment.
Ensure AI-generated content reflects sound engineering principles, appropriate safety considerations, and responsible technical communication (including "when to elevate to a licensed engineer/site expert").
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