iMerit Values

When selecting Scholars, we evaluate the following 6 values, independent of your field of study

Commitment to Quality

We ask for clear, concise communication and high-quality work. You should commit to producing thorough analysis and seeing projects through.

It requires commitment to become expert at training LLMs, and it is worth it.

How do I demonstrate a Commitment to Quality?

• Consider a new project with Scholars as the beginning of a potential career in AI training. While our work can be flexible, the more seriously you take the role, the higher quality your work will be, and the more opportunities you will gain.

• Make sure you are able to concentrate fully on your work with no distractions

• Take the time to carefully check spelling, grammar and punctuation

• If you receive quality feedback or see feedback given to others in the group, make sure you take this onboard so that your quality can increase.

Dependability

We need team members who read guidelines, meet deadlines, take responsibility for their tasks, and keep information secure. Reliability and confidentiality are key.

How do I show Dependability?

• Ensure you have sufficient time in your schedule for the demands of AI training work. While our projects are often flexible, this is often mentally-demanding work that cannot be performed successfully when you are distracted, tired or juggling other tasks.

• Read our guidelines and study them thoroughly before asking for help. We always find that candidates who read our provided information carefully will perform at a higher standard than those that do not.

• Do not leave tasks to the last minute. Candidates who start promptly and submit work on a consistent basis get feedback earlier and learn the task more quickly than others.

Flexibility

We seek individuals who adapt to new tools, guidelines, and changing processes—always ready to learn and grow in a fast-evolving field.

How do I demonstrate Flexibility?

• The world of AI is always changing. Spend a little time each week learning about new trends, and you will see the broader reason why continuous learning is essential. Read any weekly AI-related articles available in our community space.

• Learn and use technical tools reliably

• Read documentation before asking basic questions

• Stay up to date with our FAQs and new project guidelines. As projects progress, guidelines can change, so it is important to check back in regularly.

Respect & Communication

We value collaborators who welcome feedback, appreciate diverse perspectives, and contribute to a positive, supportive team environment.

We expect candidates to communicate with us and their peers, promptly, clearly and proactively.

How do I show Respect and Communication?

• Try to learn as much as possible about the project you are working on, who the team members you will need to contact, and details like deadlines and meeting times.

• For any training session or meeting, make sure you attend on time so that you do not miss information or delay other people's progress. If you miss a required meeting, you may not be able to continue a project.

• Make sure that you speak and message everyone you work with in a professional and courteous manner.

• Give others the benefit of the doubt when you are using chat messages, as it is easy for misinterpret people's intentions.

Integrity

We look for people who use rigorous, logical, and ethical reasoning—no plagiarism, no cutting corners. You should ensure your work is accurate and trustworthy.

How do I show Integrity?

• Make sure you completely understand our requirements around Plagiarism and use of AI. These are absolutely fundamental to our work.

• When providing work for us, be ready to explain your choices to justify the decisions you are making.

• Focus on breaking down complex problems into smaller, manageable steps, explicitly outlining your reasoning process, considering multiple perspectives, and regularly evaluating your intermediate conclusions to identify potential flaws.

• When a problem is too difficult or outside of your area of expertise, do not be afraid to communicate this. It is far better to admit defeat than to submit low-quality work.

Impact Awareness

Even the smallest part of AI training affects the whole. You should be familiar with the purpose behind the project you are working on, and exercise good judgment about relevance and cultural considerations, ensuring your work aligns with shared goals.

How do I show Impact Awareness?

• Ensure you fully understand the fundamental problem statement for the task that you are working on.

• Consider learning more about the broader world of AI training, so that you can understand the bigger picture. There are dozens of free video training courses that you can take (for example, this is a good entry-level video).