Discover High-Paying AI Training Jobs

Posted On 06/01/2026

The gold rush of the 21st century isn’t for a shiny metal, but for data. As artificial intelligence models become more sophisticated, they require vast amounts of human-labeled data to learn and improve.

This has created a burgeoning industry for individuals to contribute to the development of AI and get paid for it. While platforms like Mercor and Aligner have gained attention, I’ve spent time navigating several others, each with its own unique landscape of opportunities, challenges and rewards. If you’re looking to dip your toes into the world of AI training, here’s my experience with seven platforms that are worth your consideration.

1. Mercor

Mercor stands out for its innovative screening process, which uses an AI interview to evaluate candidates. It focuses on connecting talent, especially in the tech field, with AI projects.

• Types of Work: The platform is heavily geared towards specialists. Common jobs include training large language models (LLMs) in specific areas like programming, law or creative writing, as well as evaluating the quality and safety of AI responses. If you have deep knowledge in a field, Mercor is the place to monetize that expertise.
• How to Get Started: The process begins with creating a profile and submitting your resume. The crucial step is the 20-minute AI interview, which asks questions based on your resume and experience to assess your skills. Passing this interview is the key to having your profile discovered by companies.

Pros & Cons:

• Pros: The pay is highly competitive, reflecting the need for specialists. The AI interview is a unique and efficient experience for demonstrating your skills. The platform is very organized, with clear communications.
• Cons: It is extremely selective. Many people apply and are not approved or never receive a project. The AI interview can be intimidating and doesn’t allow for human interaction to ask questions about the work. The availability of projects is highly dependent on your area of expertise.

Try Mercor using my recommendation link here

2. Aligner

Aligner, connected to Labelbox, presents itself as a community of experts who train the next generation of AI. The platform attracts many with the promise of very high pay rates.

• Types of Work: The focus is on AI evaluation and training tasks that require specialized knowledge. This includes everything from assessing the quality of AI-generated text and creating prompts to test the limits of models, to audio tasks like recording your voice to train speech models. The variety is wide, with projects for cooks, engineers, musicians, and more.
• How to Get Started: The multi-step sign-up process includes identity verification and an interview with an AI interviewer named “Zara.” After that, you can apply for specific domain assessments to prove your expertise and unlock paid projects.

Pros & Cons:

• Pros: The earning potential is very high, with advertised rates that can reach three figures per hour for niche experts. The variety of projects means people from different backgrounds can find opportunities.
• Cons: The promise of high earnings generates a lot of skepticism, and the reality is that most projects pay more modest rates. The availability of work is notoriously inconsistent, and many users report spending months on the platform without landing a project. The sign-up process is long, with no guarantee of a return on the time invested.

Try Aligner using my recommendation link here

3. DataAnnotation.tech

Right off the bat, DataAnnotation.tech felt different. The platform positions itself as a place for more complex, long-term projects, and it delivers on that promise.

• Types of Work: The tasks here are a step above simple data labeling. I’ve encountered everything from evaluating the quality of AI-generated code to engaging in nuanced, long-form conversations with chatbots to test their reasoning and safety protocols. If you have a background in coding, writing or a specialized field, you’ll find more engaging and higher-paying projects here.
• Getting Started: The barrier to entry is higher than most. The sign-up process involves a series of assessments designed to gauge your skills, starting with a core qualification test and then branching into specialized evaluations for coding or specific subject matter expertise. You need to pass these to unlock access to projects.

Pros & Cons:

• Pros: The pay is arguably among the highest in the industry, often ranging from $40+ per hour. The work is genuinely interesting and makes you feel like you are contributing to the cutting edge of AI development. The platform is straightforward, with clear instructions and a responsive support team.
• Cons: The initial assessment can be challenging and time-consuming, with no guarantee of being accepted. The availability of projects can fluctuate, and you might experience periods of no work, especially if you haven’t qualified for the more specialized tasks.

4. Remotasks

Remotasks is often a starting point for many, and it was for me as well. It’s a massive platform with a constant flow of work, powered by the industry giant Scale AI.

• Types of Work: The bread and butter of Remotasks is data annotation in its many forms. This includes 2D and 3D image and video annotation (drawing boxes around objects), LiDAR annotation for self-driving car data, categorization, and transcription. They offer a wide variety of projects, catering to different skill levels.
• Getting Started: Signing up is simple. You create an account and can immediately access the Remotasks University, which offers free, albeit sometimes tedious, training courses for different project types. Passing these courses unlocks paid work.

Pros & Cons:

• Pros: There is almost always work available, making it a reliable option for those looking to start immediately. The entry barrier is very low, and the training, while sometimes dry, does prepare you for the tasks. It’s a great place to learn the fundamentals of data annotation.
• Cons: The pay can be quite low, especially for the simpler tasks, and is often paid per task rather than per hour. This can lead to earning significantly less than minimum wage when you’re starting out. The platform’s interface can sometimes be buggy, and getting support can be a slow process.

5. Appen

Appen is a veteran in this space, and its platform feels more like a traditional job board for flexible, remote work rather than just a micro-task platform.

• Types of Work: Appen offers a very broad range of projects. I’ve seen long-term social media evaluation roles (requiring a few hours of work per day), data collection projects (like submitting photos or voice recordings), transcription, and translation services.
• Getting Started: You create a profile and then apply for individual projects that interest you. Each project has its own set of requirements and may require you to pass a specific qualification test. The process can be slower than on other platforms.

Pros & Cons:

• Pros: The variety of projects is a major plus, going beyond simple annotation. You can often find longer-term projects that offer more stable work. Pay rates are generally decent and clearly stated in the project descriptions.
• Cons: The application process for each project can be cumbersome, and you might apply for several before getting accepted. The platform’s communication can sometimes be inconsistent, and the payment system, which often runs through Payoneer, can be less streamlined than direct deposits.

6. Clickworker

Clickworker operates on a crowdsourcing model, offering a vast number of “micro-tasks” that can be completed quickly. It’s less focused on complex AI training and more on a broad range of small digital tasks.

• Types of Work: The tasks are diverse and often simpler. I’ve worked on things like text creation, data categorization, proofreading and participating in surveys. They also partner with other platforms, so you might find yourself doing image annotation or data validation tasks for AI clients.
• Getting Started: The sign-up is straightforward. After registering, it’s highly recommended to complete your profile fully and take the available assessments. A higher assessment score unlocks more and better-paying jobs.

Pros & Cons:

• Pros: The sheer volume and variety of tasks mean there’s usually something to do. The platform is user-friendly and offers flexibility to work whenever you want, for as long as you want. The payment process is reliable.
• Cons: The pay per task is very low. You need to be extremely fast and efficient to earn a meaningful amount of money. The more lucrative work is often snapped up quickly, so you need to check the platform frequently.

7. Neevo by Defined.ai

Neevo is another platform focused on human-powered AI training, with a clean interface and a global user base.

• Types of Work: The projects are heavily focused on data collection and annotation. I’ve had tasks that involved recording short phrases in my native language, transcribing audio clips and labeling images to help train computer vision models.
• Getting Started: Registration is easy. Once you’re in, you’ll be presented with available jobs that match your language and skills. Before starting a project, you typically have to go through a short, simple qualification test to ensure you understand the instructions.

Pros & Cons:

• Pros: The platform has a very clean and intuitive user interface, making it easy to navigate. The instructions for jobs are generally clear and concise. It’s a great option for those who are multilingual, as they often have projects specific to different languages.
• Cons: The biggest drawback is the inconsistent availability of work. There can be long dry spells with no projects available. The pay per task is on the lower end, so it’s more of a side hustle for extra cash rather than a primary source of income.

Conclusion: Who Is This Work For?

After navigating these seven platforms, it’s clear that AI training work is not a one-size-fits-all solution. So, who is it recommended for?

1. For Experts and Professionals: If you have deep knowledge in a specific area (be it programming, medicine, law, or even a hobby like woodworking), platforms like DataAnnotation.tech and Mercor are ideal. They offer the best compensation and the most intellectually stimulating work, allowing you to directly capitalize on your experience.
2. For Beginners and the Curious: If you’re just starting and want to learn the basics of data annotation without needing prior experience, Remotasks and Clickworker are excellent starting points. The barrier to entry is low, and there are always tasks available. However, go in with realistic expectations about earnings — think of it as a way to make some extra money while learning a new skill, not as a job replacement.
3. For Those Seeking Flexibility and Variety: Platforms like Appen and Neevo are a good fit for those looking for a wider variety of tasks beyond annotation, such as social media evaluation or data collection. They offer flexibility, but, much like Aligner, the consistency of work can be an issue. They are best suited as a source of supplementary income.

In short, working in AI training can be a fascinating and lucrative opportunity, but it requires patience and choosing the right platform for your profile. It’s a field that rewards specialization but also offers an entry point for those willing to start with the basics. The secret is not to put all your eggs in one basket and to treat it for what it is: project-based work, with its ups and downs, in the exciting landscape of the artificial intelligence revolution.