LinkedIn is offering members an opportunity to earn flexible, skill-based income using their expertise to help companies develop high-quality, human-labeled data to train their AI systems. We’re slowly rolling out this experience to members and will grow its availability as we collect feedback from our members. This initiative reflects our commitment to creating economic opportunities for every member of the global workforce.
Important to know
We’re gradually making this experience available, and you might not have access to it at this time.
Check out some frequently asked questions below.
Who can become an AI trainer?
While any LinkedIn member can express interest in becoming an AI trainer, we do require you to complete a few steps to meet minimum eligibility requirements:
- Verify your LinkedIn profile with a government ID.
- Converse with LinkedIn’s AI Project Matching Assistant to share more about your expertise.
- Complete project-specific tasks (varied based on the projects).
How do I apply to become an AI trainer?
You will see prompts across LinkedIn inviting you to learn more and express interest.
Is annotation work paid?
Yes, paid projects will become available starting in 2025. If hired, you will be compensated for the tasks you complete. Actual pay will vary by client and project.
Actual pay will vary by client and project.
How will LinkedIn vet if I have the skills to be an AI trainer?
There are two ways in which LinkedIn will determine if you have the skills to be an AI trainer:
- AI trainer skills assessment: The AI trainer skills assessment will determine your ability to complete the tasks you may have assigned to you in an AI Trainer project.
- Example: An evaluation task - Reading an AI response and judging how good it is. You're given a prompt and the AI's answer, and you score it on things like accuracy, helpfulness, and safety. Think of it as being a quality inspector for AI outputs.
- AI-powered conversation: This feature uses AI to ask you questions about your professional background and respond to your answers, simulating a realistic conversation. Your conversation data and related AI insights will be used to supplement the information already on your LinkedIn profile so that we can better match you to relevant AI training projects based on your experience and expertise and assess your fit for specific projects. We will also use this information to suggest updates to your LinkedIn profile. We will not use this information for other purposes without your permission.
- You must answer at least 3 questions for the AI-powered conversation to be considered complete.
- AI-powered conversation is powered by Microsoft’s Azure OpenAI API Service to develop a contextual understanding of the scenario and uses a finely tuned dialogue prompt to conduct a realistic, appropriate conversation. Microsoft’s Azure AI Speech is used to convert text responses into audible voice responses, and vice versa.
How does the AI trainer skills assessment work?
The assessment is designed to evaluate baseline annotation competencies that are commonly required across AI Trainer projects. The assessment includes questions across five core annotation task types:
Each question presents a prompt or scenario related to evaluating or improving AI-generated responses. You’ll enter your responses in written text format directly within the assessment interface. All answers must be completed before the assessment can be submitted. If any fields are left blank, the system will prompt you to complete them prior to submission.
You may:
- Save your progress and return to a partially completed assessment at any time prior to submission.
- Download your submitted Q&A responses.
- Delete an attempt and retake the assessment if needed.
- Once submitted: Your attempt is locked and cannot be edited.
The assessment validates general annotation fundamentals. It does not measure domain-specific expertise or guarantee performance in a specific project environment.
How are my assessment results used and stored?
Assessment results are:
- Viewable by hiring teams when you apply to an AI Trainer project
- Used alongside other signals such as domain expertise and education level to support hiring
When you complete the assessment, the system generates structured results that reflect your performance across different annotation skill areas.
- Each question receives a rating based on:
- Questions are evaluated using a scoring scale; for example, a 1–5 scale
- Scores are calculated:
- Per question
- Per annotation skill type (Evaluation, Preference Ranking, Rubric Work, SFT Work, Agentic Work)
Integrity signals (such as large copy and paste events) may also be captured at the assessment level to help identify potential misuse.
Your assessment results are shared with the hiring team supporting the AI Trainer project(s) you apply to. They may also be reviewed by LinkedIn for quality evaluation and product improvement.
How will LinkedIn vet for domain expertise?
For projects related to your specific expertise (e.g., law, medicine, finance), LinkedIn will use your profile data, such as education, licenses, and work experience, as well as an AI-powered informational conversation where you can share your experience in more detail. We will use this information to match subject matter experts to the right tasks and evaluate your fit for a project.
Important to know
While our goal is to create a seamless AI-powered conversation, it’s important to know that information provided by AI could potentially be limited or contain inaccuracies. Any AI responses related to third parties (i.e., compensation details, response timelines, or project duration) should be verified directly with the third party.
How will I be informed about new projects or opportunities?
You can opt in to receive notifications and alerts for upcoming annotation projects. You’ll be automatically matched to opportunities that fit your expertise.
Learn more