Chemical Engineer: AI Model Evaluation & Technical QA

SME Careers; Australia; On-site; AUD 90,000 - 130,000; Full time

Job summary

SME Careers is seeking a chemical engineer to critically evaluate AI-generated content across chemical engineering topics, including material and energy balances, phase behavior, and process control. You will challenge models with real-world scenarios, review responses, and provide actionable feedback to improve model quality and safety.

The role emphasizes rigorous engineering judgment, defensible assumptions, and clear communication, with potential collaboration across data training projects

Qualifications

• Bachelor’s degree in Chemical Engineering required; advanced credentials strongly preferred.
• 4+ years of professional chemical engineering experience with process design and operations.
• Strong ability to perform engineering calculations, justify assumptions, and reason under uncertainty.

Responsibilities

• Evaluate AI-generated technical content for accuracy and clarity in chemical engineering.
• Provide structured feedback on errors, incomplete reasoning, or unsafe recommendations.
• Review and refine AI prompts, model responses, and step-by-step engineering solutions.
• Help shape AI communication standards for technical chemical engineering content.
• Identify safety considerations and escalation needs when appropriate.

Skills

Process design

Plant/Operations engineering

Process safety

Scale-up

Engineering calculations

Controls/automation interfaces

Education

Bachelor's degree in Chemical Engineering

Master’s/PhD or professional credentials

Tools

PFDs/P&IDs

Aspen Plus/HYSYS

CHEMCAD

PSM documentation

HAZOP/LOPA

SOPs

Job description

SME Careers is seeking a chemical engineer to critically evaluate AI-generated content across chemical engineering topics, including material and energy balances, phase behavior, and process control. You will challenge models with real-world scenarios, review responses, and provide actionable feedback to improve model quality and safety.

The role emphasizes rigorous engineering judgment, defensible assumptions, and clear communication, with potential collaboration across data training projects