AI Trainer — Remote Real Estate Evaluation (Part-Time)

LinkedIn; United States; On-site; USD 83,000 - 165,000; Part time

Job summary

LinkedIn seeks contracted AI trainers with strong Real Estate and Rental and Leasing expertise to design authentic evaluation tasks for training LLMs. You will craft real-world scenarios, scoring rubrics, and clear evaluation criteria to ensure high-quality model outputs.

This is a part-time, project-based engagement with remote work options. Consultants control their schedule and data-handling practices while contributing to AI safety and accuracy in real-world contexts.

Qualifications

• Based in the United States.
• Substantial experience in Real Estate and Rental and Leasing.
• Ability to create tasks across multiple occupations.
• Strong analytical and professional writing skills.
• Experience reviewing, supervising, auditing, or evaluating work preferred.

Responsibilities

• Create original, real-world professional tasks for Real Estate and Rental and Leasing.
• Develop clear prompts with realistic requirements, constraints, and expected work products.
• Create scoring rubrics or evaluation checklists.
• Define essential success criteria and material response failures.
• Apply professional judgment to make tasks challenging and representative.
• Cover multiple occupations within the industry.
• Review model responses and document deficiencies.
• Revise submissions based on reviewer feedback.
• Ensure submissions exclude confidential, proprietary, privileged, or personally identifiable information.

Skills

Real estate expertise

Analytical writing

Evaluation criteria

Quality review

Job description

LinkedIn seeks contracted AI trainers with strong Real Estate and Rental and Leasing expertise to design authentic evaluation tasks for training LLMs. You will craft real-world scenarios, scoring rubrics, and clear evaluation criteria to ensure high-quality model outputs.

This is a part-time, project-based engagement with remote work options. Consultants control their schedule and data-handling practices while contributing to AI safety and accuracy in real-world contexts.