Strong growth but be thoughtful about your risk tolerance! - Anonymous employee Mercor Employee Review

I joined as a contractor and worked on a data annotation project. It was a great experience. There were several team leads and coordinators who were ready to answer questions and support the project, which impressed me. A very good structured crew with great mutual respect. It took me a few hours to go through guidance and get familiar with the domain tasking before I was able to start my first task. Then I climbed up my learning curve and contributed to many tasks. It was very decent hourly rate, and I earned a good number to cover my living cost. I devoted about ~20 hours to this project every week, while I also worked on my other routines and other job. No conflicting and very good flexibility as WFH. I also feel it is a rewarding experience as this is my first time to get a hands-on experience of real AI annotation while contributing my technical expertise (STEM major).

The project was seasonal and it did require quite a bit of learning curve. For some domains, you may have no sufficient tasks to do all the time. This project lasted for few weeks. You don't know if there will be another similar project to do (and make money) after this wrapped up.

Mercor provides access to a wide range of AI-related projects including evaluations, data labeling, rubric grading, and prompt/world generation, which makes it a great way to gain hands-on experience in the AI space. The onboarding process is smooth, and there is strong operational support through tools like the Melvin chatbot as well as EPMs who oversee projects and provide guidance when needed. Pay is competitive, and weekly payouts are a major advantage. For someone looking for flexible, project-based work rather than a traditional full-time role, it can be a valuable opportunity to build skills and stay active in the AI ecosystem.

Work is not consistent or guaranteed, and project availability can be competitive. Most roles are short-term or variable in duration, which means income and workload can fluctuate significantly. While there are now some full-time project opportunities, they tend to be highly competitive and dependent on location and prior experience. Matching to projects aligned specifically with one’s background isn’t always guaranteed, though skill-based matching does improve over time.