Industrial Engineer, AI Training and Evaluation

Industrial Engineer, AI Training and Evaluation at Braintrust

Your final hourly rate will be chosen by our client and determined by your location.

Fluent French/English Required

We’re seeking an Industrial Engineering expert to support the evaluation and improvement of large language models (LLMs). In this role, you’ll review, critique, and help design high-quality annotations, datasets, and evaluations created by other contributors—ensuring technical accuracy, rigorous reasoning, and clear explanations across complex Industrial Engineering domains.

This is a hands-on expert role focused on judgment, analysis, and clarity rather than data entry or model training.

Required Qualifications

• Master’s degree or PhD in Industrial Engineering or a closely related field
• 5+ years of research or industry experience applying Industrial Engineering methods
• Strong understanding of core domains, including:
• Operations research
• Optimization methods
• Supply chain systems
• Manufacturing and production systems
• Quality engineering and process improvement
• Fluency in English and French, with the ability to read, write, and critique complex technical material in both languages
• Ability to critique, explain, and improve complex technical content in clear, precise language
• High attention to detail and comfort evaluating nuanced reasoning and tradeoffs

Preferred Qualifications

• Research or industry experience in:
• Optimization, simulation, or systems engineering
• Workflow analysis or industrial system modeling
• Familiarity with analytical or programming tools such as Python, R, MATLAB, or similar
• Experience reviewing, teaching, or documenting technical material
• Experience evaluating or translating technical concepts across English and French contexts
• Prior experience with data annotation, evaluation, or AI/ML-adjacent workflows is a plus

What You’ll Be Working On

You’ll support the training and evaluation of AI large language models (LLMs) by reviewing, critiquing, and improving Industrial Engineering–focused content for technical accuracy, reasoning quality, and clarity.

Your work may include:

• Reviewing and evaluating AI-generated explanations of optimization, forecasting, and system design
• Assessing analyses related to supply chain networks, operations research, and manufacturing systems
• Validating methodologies, calculations, assumptions, and multi-step reasoning
• Reviewing step-by-step problem-solving for correctness, completeness, and logical consistency
• Writing or refining clear explanations of engineering tradeoffs and decision logic
• Annotating and labeling complex content (text, math, code, or technical explanations) using detailed guidelines
• Evaluating model outputs for accuracy, edge cases, failure modes, and reasoning quality
• Designing and reviewing prompts, questions, and test cases to stress-test model capabilities
• Performing head-to-head model evaluations to identify strengths, weaknesses, and regressions
• Identifying ambiguity, bias, or systematic errors and providing structured, actionable feedback
• Contributing domain expertise to refine annotation schemas, evaluation criteria, and benchmarks
• Clearly documenting decisions and rationale to ensure consistency, auditability, and reproducibility
• Collaborating with engineering, product, and research partners to improve overall model performance

Key skills/competency

• Industrial Engineering
• Large Language Models (LLMs)
• Operations Research
• Optimization Methods
• Supply Chain Systems
• Manufacturing Systems
• Quality Engineering
• Process Improvement
• Data Annotation
• AI Evaluation