The process from start to first task

One of the most important things to understand, especially if you’re new to Mindrift, is how things work around here. From payments to security and onboarding, we’ve got you covered.

What happens between my application and first task? 

From submitting your CV to joining a project, we’ve got you covered — with insights from one of our Acquisition Specialists. 

Shedding light on how projects work

Get answers to some of our most asked questions around the project lifecycle, downtime, task availability and more, with insights from over 200 Mindrift AI Trainers. 

A guide to identity verification

Explore every aspect of identity verification — from who handles your data to why we require verification at all — to help you navigate the process with confidence.

Top 3 onboarding mistakes (and how to avoid them)

We asked Simon, a Senior QA at Mindrift, to share the top onboarding mistakes he sees again and again (and most importantly, how to avoid them). 

Everything you need to know about payments at Mindrift

We’ve gathered some of the most frequently asked questions regarding compensation and payment rates to build more transparency around the process. 

How Mindrift keeps your data safe

Learn how we collect, use, store, and protect contributor data, with insights from Oleg, our Security and Compliance Manager.

How quality assurance shapes better AI

Dive into what QAs do at Mindrift and how their input helps AI Trainer shape better models. 

4 things we wish more trainers knew

Some key truths about how the Mindrift platform works, with advice from Simon, a Senior QA at Mindrift. 

Project deep dives

Now that you have a good overview of the Mindrift application and project process, it’s time to explore how projects actually work. Ready about two very different types of projects to see what real contributions look like. 

Human preferences and when “too helpful” becomes a problem

Discover some lessons we learned from a human preferences training project, as well as how the project process worked and practical training tips. 

Red teaming: What does it take to outsmart an AI model?

Get an inside look at the minds of malicious users, the importance of AI safety training, and how being believably bad is actually very hard with an in-depth look at a recent red teaming project. 

Guides for tricky situations

AI Training might be a meaningful and interesting gig, but it’s not always easy. Tricky situations often pop up and stump new and experienced AI Trainers alike. Learn how to handle a few common, yet complex, scenarios. 

What to do when there’s no clear answer

Learn how to recognize and handle ambiguity on projects, because sometimes there isn’t always a “correct” answer — the right response often depends on subtle context, tone, or user intent.

Understanding your audience

No matter how advanced an AI model is, it won’t hit the mark if it doesn’t understand who it’s built for. Get practical tips for understanding your audience. 

AI hallucinations: Why do models make stuff up?

Take a look at why AI gets creative with its answers, how it can go from helpful to harmful, and what AI tutors can do to keep things on track.

Learn from our community

There’s no better way to learn about the AI training process than from our community — the people completing tasks and shaping the future of AI every single day. 

Tristan, QA

“From my first interactions with Mindrift, it was obvious that you'd actually be able to create human connections while working on building machine intelligence.”

Simon, Senior QA

“I think we’re in a phase of rediscovering the need for human refinement. Early LLMs relied on raw big data, but quality suffered. Now, human oversight is more important than ever.”

Roman, QA

“If I had to pick one unexpected aspect of working with AI, it would be the sheer amount of data, effort, and people involved in such projects.”

Chloe, QA

“I’m passionate about AI and technology! I feel empowered by AI in many aspects, from exploring complex and foreign fields using a good knowledge base to improving efficiency in my professional work. I’ve always wanted to be not only a user, but also a creator in the digital world.”

Faith, Editor

“I joined Mindrift in Spring 2024, and it's been a fascinating journey. As a copywriter, I'm captivated by large language models (LLMs), so when an opportunity arose to be an editor at Mindrift, I jumped at the chance.”