1. Learn about the field

Don’t assume you need to be a tech expert to work with AI models, but it’s great to have a basic understanding of the field. Many of our AI Trainers and Quality Assurance (QA) specialists had some previous interest in, and even experience with, AI models prior to joining Mindrift platform. 

That being said, if you’re starting from zero, that’s okay too! We’ve got tons of great content over on our blog to get you inspired:

• Break down the key principles of AI training

• Learn about the evolution of GenAI models

• Explore why human intelligence is essential for AI 

Understanding the basics of how GenAI models work and what goes into AI training will also help you succeed once you’re actively contributing. 

“I would advise someone interested in AI training to understand how AI processes information differently from humans. Sometimes you need to break down the knowledge points to feed AI piece-by-piece. The process takes patience and time,” explains Chloe, a QA at Mindrift. 

2. Set realistic expectations

A lot of our AI Trainers, from  mathematicians to lawyers to mechanical engineers, are experts in their field. Unfortunately, being an expert doesn’t automatically make you good at AI training. 

It’s important to go into AI training opportunities with an open mind and realistic expectations. Training models in your field of knowledge doesn’t always involve the same tasks and workflows you’re used to. Most AI training projects focus on writing and editing text while following strict guidelines. 

“An AI Trainer is responsible for creating question-answer pairs, dialogues, tasks, solutions, and other text-based prompts that will later be used to train an AI model. Imagine explaining a scientific topic to a friend or student, solving a math problem, or writing a brief article about a medical case or historical event. These are the kinds of tasks you can expect,” explains Roman, a QA at Mindrift. 

To make sure your expectations line up with reality, learn about the basics concepts of AI Training before jumping in. 

3. Expect to be challenged

Side hustles are supposed to be easy, right? Not in the case of AI training. 

Of course, AI training can be very enjoyable and fulfilling! You’ll get the opportunity to contribute to exciting, cutting-edge projects, collaborate with people around the world, and learn more about the mechanics of AI technology. But it’s not something to consider if you’re looking for mindless, quick money-making tasks. 

AI Trainers at Mindrift often find the projects satisfyingly challenging. You’ll have to sift through complex guidelines, get used to new workflows, collaborate with different types of people, and harness your creativity to succeed. 

“The biggest challenges come with complex projects, where the learning curve takes weeks. There are strict deadlines, which can result in long hours of work that might drain you by the end of the project. That happened to me on one occasion. To deal with it, I asked to do fewer projects for a few weeks or to take a short break,” says Alexander, a QA at Mindrift. 

4. Set yourself up for success with onboarding

We know you might be excited to jump into a project, but skimming through the onboarding process without retaining critical information is a bad idea. 

Onboarding is a necessary requirement for every single project, no matter how many times you’ve contributed, because every client has unique requirements. Even projects that sound similar initially might have one or two specific differences that change the entire focus and scope of the project. 

“Experts often skim guidelines because they don't see them as important, but in reality, writing quality and strict compliance with instructions are critical,” confirms Simon, a QA at Mindrift. 

Not only does onboarding help you understand the needs and expectations of the project, but it also ensures your submitted tasks are following the guidelines. Quality and accuracy during task submission is crucial for approval and prompt payment. 

5. Use feedback to your advantage

Our AI Trainers are never micromanaged or treated like employees because this is a freelance, project-based opportunity. That being said, you’ll sometimes receive feedback from our QAs, fellow trainers who ensure projects run smoothly and quality stays on top.

The difference between AI Tutors and QAs at Mindrift

“One challenge is that we now recruit domain experts, but expertise in a field doesn’t automatically translate to success in AI tasks. For example, a PhD in medicine doesn’t mean someone can craft effective LLM prompts. This disconnect leads to frustration when experts struggle with the tasks and fail to meet requirements,” says Simon. 

Use feedback to improve your skills, ensure you meet requirements, and learn from the experts. AI Training can come with a bit of a learning curve and any feedback provided by our QAs is meant to help, not hinder you. And while feedback sometimes does come up, it’s important to note that individual, consistent feedback isn’t something you’ll encounter.  

6. Brush up on your language and grammar skills

A large part of what our AI Trainers do is writing and editing text. Strong language and logic skills really help. We recommend testing your writing, language, and grammar skills ahead of time.

We’re extremely focused on working with people who embody these skills so you’ll definitely encounter a language test if you apply to contribute to Mindrift. We’re not necessarily looking for native speakers but clarity is key when working with AI models. 

As an AI Trainer, one of your key goals is to encourage natural-sounding, accurate responses from the AI models. It should sound like a conversation with a friend—not a robot. That’s why a strong knowledge of the required language is critical. 

7. Understand that project availability can be unpredictable

One of the most common pieces of feedback we get is that project availability is unpredictable. Some AI Trainers complete one project and hear nothing for months, others contribute consistently—so what’s the deal? 

An overview of Mindrift’s immediate projects vs. talent pool

The truth is, project availability is unpredictable. Expect that opportunities can be a one-time project or there might be pauses between projects. On platforms like Mindrift, project availability depends on the client’s needs. They might need a very niche, small group of experts for an extended project or a large number of generalists for a short opportunity. 

“I would say manage your expectations because projects are very much dependent on the client's requirements. But I think it's a privilege to be able to work on projects like this,” confirms Tristan, a QA at Mindrift. 

Learn more about the project lifecycle at Mindrift to ensure your expectations are realistic. And remember, it’s a flexible, project-based opportunity and a great additional source of income, but it’s not a guaranteed full-time role.

8. Join our diverse community

Mindrift encourages professionals from around the world to contribute to our projects, which has led to us building a very fun, diverse community of experts. We encourage new AI Trainers to get involved any way they can. 

“There’s a very interesting and enriching aspect of this job: working on different projects and getting insight into how people from different fields interact and interpret the world. It’s been kind of eye opening,” explains Tristan. 

From Discord to forums to blog contributions, active involvement benefits everyone. You get to experience a new community and network with experts in your field, and we get to know you a little better! Plus, peer support and shared tips really help with motivation and consistency.

9. Treat it with care 

AI depends on your judgment, which means treating AI training opportunities with care and respect is key. At Mindrift, we focus on advancing AI models with three core values in mind:

• Honesty

• Helpfulness

• Harmlessness

In practice, this means that quality matters more than speed. We know it might be tempting to rush through tasks in order to finish faster and move onto the next, but your goal as an AI Trainer is to teach the model how to think—and that requires time and mindfulness. 

Rushing through tasks, completing them carelessly, or using automations doesn’t benefit anyone. It might mean an account violation for you, or a rejection of your tasks that results in lost payments. Most importantly, it doesn’t help the purpose of advancing AI models. 

10. Stay curious 

“I highly recommend this role to someone who is open-minded to upcoming changes, passionate about technology, brave enough to embrace uncertainties, patient with training, and generous with sharing knowledge,” says Chloe. 

Curiosity and openness to new experiences will make your journey at Mindrift more enjoyable—and successful! 

The AI field is evolving very quickly and things change every single day. Projects pop up when least expected, others are put on hold without warning, new requirements can arise, and innovative breakthroughs can change the entire course of technology. Being curious and eager to learn are strong indicators of success at Mindrift.