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- Tasks: Evaluate and improve AI models in Industrial Engineering, ensuring accuracy and clarity.
- Company: Join a forward-thinking tech company focused on AI advancements.
- Benefits: Competitive pay, flexible hours, and opportunities for professional growth.
- Why this job: Make a real impact in AI while utilising your engineering expertise.
- Qualifications: Master’s or PhD in Industrial Engineering and 5+ years of relevant experience.
- Other info: Collaborative environment with a focus on innovation and career development.
The predicted salary is between 13 - 16 £ per hour.
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.
Your final hourly rate will be chosen by our client and determined by your location.
Responsibilities- 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
- 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
- Research or industry experience in:
- Optimization, simulation, or systems engineering
- Workflow analysis or industrial system modeling
Industrial Engineer - AI Training / Evals / Data Review employer: Braintrust
Contact Detail:
Braintrust Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Industrial Engineer - AI Training / Evals / Data Review
✨Tip Number 1
Network like a pro! Reach out to your connections in the Industrial Engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts clearly, as you'll need to demonstrate your expertise in areas like optimisation and supply chain systems.
✨Tip Number 3
Showcase your bilingual skills! Since fluency in French and English is a must, be ready to discuss your experiences in both languages during interviews. This will set you apart and highlight your ability to critique technical material effectively.
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're serious about joining our team and helps us keep track of your application.
We think you need these skills to ace Industrial Engineer - AI Training / Evals / Data Review
Some tips for your application 🫡
Show Off Your Expertise: Make sure to highlight your qualifications and experience in Industrial Engineering. We want to see how your background aligns with the role, so don’t hold back on showcasing your skills in operations research, optimisation methods, and supply chain systems.
Be Clear and Concise: When writing your application, clarity is key! Use straightforward language to explain your experiences and how they relate to the job. Remember, we’re looking for someone who can communicate complex ideas simply, so keep it sharp and to the point.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the role. Mention your fluency in both French and English, and how that will help you in evaluating technical content across languages.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Braintrust
✨Brush Up on Your Technical Knowledge
Make sure you're well-versed in the core domains mentioned in the job description, like operations research and optimization methods. Review key concepts and be ready to discuss how you've applied them in your past work.
✨Prepare for Language Proficiency
Since fluency in both French and English is crucial, practice explaining complex technical material in both languages. You might be asked to critique or translate content, so being comfortable in both tongues will give you an edge.
✨Showcase Your Analytical Skills
Be prepared to discuss specific examples where you've evaluated methodologies or validated calculations. Highlight your attention to detail and how you've approached problem-solving in previous roles, especially in nuanced scenarios.
✨Familiarise Yourself with AI Evaluation Processes
Understand the basics of AI model evaluation and be ready to discuss how you would approach stress-testing model capabilities. Familiarity with data annotation and evaluation workflows will also be beneficial, so brush up on any relevant experience you have.
