In today's era of AI, there's a new job that was non-existent ten years ago — one that pays a person to teach a machine to think, write, reason and respond like a human. Jobs such as AI trainer, data annotator, prompt evaluator, RLHF rater, and linguistic reviewer are no longer confined to a few roles in the United States, the United Kingdom, Canada, Australia, Germany or anywhere else; they're in high demand all over the world — and can be worked remotely with flexible pay.
Here's what you should know; most applications are filtered out long before a recruiter even sees them. AI training companies like Outlier, DataAnnotation, Appen, TELUS International AI, Invisible Technologies, Mindrift and Surge AI have created multi-layer screening processes to ensure that only serious, qualified candidates are being considered.
What are they looking for in the first pass? It is usually not as expected. It's not your years of experience! Believe it or not, it is not even your degree, in most cases. The first is much more mechanical, and comprehending them alters the way you should approach your application altogether.
Why Most Applications Do Not Get Past Screening
It's important to understand why the filtering is so strict in the first place before we dive into what AI training companies look for.
It is not a job in a single office that these companies are hiring for. They're developing on-demand, distributed teams of thousands of contributors from around the world, in various time zones, languages and skill sets, to drive the training pipelines of large language models. One project may require 500 people who have experience in organic chemistry, another may require native German speakers who have legal writing experience, another may require individuals who can just tell if a response "sounds human."
All but very little of what happens in the early stages of an application is read by a human being in the role of recruiter. It is evaluated by systems and brief qualification tasks for quick answers to the question of whether this person can work reliably at a professional level without being supervised, and can follow precise instructions.
What AI Training Companies Look For First
1. Ability to follow instructions closely
This is by far the first filter. These companies want to know that you read every word and followed instructions carefully and exactly, not roughly what's asked, not what you assumed was asked.
The application forms and qualification tests are purposely designed with numerous specific instructions: formatting guidelines, word counts, a required sequence of responses, and sometimes even an instruction to include a specific word in the answer hidden a longer passage. This isn't a trick for the sake of being tricky, but it is a trick that is needed. Real-life representation of the actual job. All day long, AI trainers have to follow guidelines for tasks that are painstakingly precise and vary from project to project, and you have to prove it, before day one anyway, that you won't skim and guess.
2. Written English (or target language) Proficiency
Whether it's not a writing project, most AI training work is done via written communication. You are reading instructions for tasks, writing feedback, giving points, marking up problems, giving explanations. Whether or not the position is described as a "writing" position, language ability is almost always considered first and assessed hard.
This matters for global audience. As a rule, employers in the UK, USA, Canada and Australia look for near-native or native English speakers who have the correct grammar, a natural style of speaking and can write clearly without coming across as over-explaining. The same would be tested by companies that are recruiting in Germany, France or other non-English markets for localized model training, possibly in conjunction with English for cross team communication.
What They're particularly checking for:
- Grammar and punctuation accuracy
- No unusual or over complicated sentence constructions.
- Clarity and conciseness.
- The use of consistent spelling, both UK and US English (where applicable to the project).
- Does your writing convey a natural tone and such a level of confidence that it doesn’t sound like a translation or a copy and pasted script?
If you have one or two answers that are grammatically incorrect in your application i's not disqualifying on its own, but if you have multiple answers that are grammatically incorrect, it's a problem. These systems are designed to detect patterns.
3. Relevant Domain Expertise/Subject matter background
Once basic qualifications are confirmed, the next hurdle most AI training companies have to clear is more specific expertise related to the project they're staffing. This is where your educational and certification courses comes into play, and it may be more important than for a regular application for a job.
Projects usually need people for projects in:
- Legal, financial, medical, nursing or other licensed professions
- Software engineering, data science or programming languages
- Academic writing, journalism or editing.
- Mathematics, physics or other STEM discipline
- Technical trades and industries with a niche interest.
If you have a degree, certification or a number of years of experience in a specific field, that can be your best asset in this whole process, more so than your general work history. When signing up for many AI training platforms, they will ask you what you are good at and assign you to projects that are similar to that. Here, being honest and specific is more likely to get you more opportunities, not less: specificity is an indicator of credibility.
4. Identity, location and work eligibility
This is no glamorous part, but it's one of the first hard filters to fail, and it is one of the most common reasons for applicants to fail all over the world. AI training companies have to verify your identity and legal working location, as most of them are independent contractor platforms with taxation and legal requirements based on your nation of citizenship.
Be prepared to get some of the following:
- Government-issued ID verification
- Address (or) Residence confirmation
- Tax form appropriate to your country (e.g. a W-9 form for a contractor from the US, or a similar form in another country)
- Confirmation that the job is available in your particular country because many projects are location-specific.
This is no trust problem, it is a legal requirement. However, it is important to know, at the start of an application, that the country of origin may not be in the list for a specific project, and that can stall your application since the applicant country isn't open for the given project.
5. Performance in the qualification assessment
Almost all reputable AI training companies have a qualification exam or interview, prior to allowing access to the tasks. This is the actual interview. It typically contains a combination of:
- Multiple choice questions testing comprehension and judgement
- Brief written answers to questions that assess logic and tone
- Sample tasks that are similar to real project tasks, including comparison tasks and explanations of why one answer is better than the other (2 AI-generated answers compared to each other for example)
They're not only scoring this for correctness. They are measuring your reasoning, consistency and your judgment according to their own quality standards. A candidate may obtain a few answers "incorrect" but demonstrate clear and well-reasoned thinking, and may have a higher score than a candidate who has a few answers "correct" but is lacking in clear and well-reasoned thinking. Transparency of reasoning is important because the companies have to have confidence that your judgement will be transferable to thousands of tasks that you have not yet performed.
6. Consistency and attention to detail, and not speed
One common error students make when applying to a program and/or taking the test is rushing through the assessment stage to get in as quickly as possible. In this situation, AI training companies are rewarding carefulness not speed. They're keeping their eyes out for carelessness: inconsistent answers, contradictions between parts of a form, typos in important parts of a form, sub-questions that are not answered.
It's like previewing how your work will look in the application and how it will look in the real world. If you're inconsistent when there's no project on it, you will likely be inconsistent when there's a real project on it. The act of slowing down to read each section twice, carefully is one of the highest leverage things that you can do before you submit.
7. Demonstrate professional and human writing style in your written response
A newer and more important filter these days – particularly in the past 2 years – is your written response. So many of the applications are now utilizing AI tools to write their answers that some training companies are actively checking for generic AI generated phrases; overly polished phrases, repetitive sentence structures, buzzwords, and any answer that sounds like it was cut from a template.
It's relevant to this industry and more than any other, as the whole reason for the role is to make AI sound less robotic and more human. If your own application sounds like a chatbot, then the skill that the role is testing is being undermined. Write in your own words. Be specific.
Common Mistakes That Sink Otherwise Qualified Applicants
Ignoring or overlooking instructions that are in a standard form.
Sending a generic CV or cover letter to multiple jobs that are unrelated
Exaggerating skill sets that you don't really have when task level work begins.
When the applicant's English is really good, but the grammar errors are numerous, caused by haste.
Applying to every role that opens up rather than applying for two or three jobs that match your skill sets.
Providing general, "safe" responses in the qualification exam where concepts of reasoning or explaining is needed.
None of these are about ability. They're about approach. Most rejections are due to someone's application that's too quick and in a rush.
Getting Ready Before Applying
The best applicants don't think of it as a form to fill out, but rather as a true assessment. There are a couple of things to do in advance:
Refresh your written bio and any sample writing so as to make it sound like a confident and clear voice of a human being, not a template.
Honorably list your genuine area of expertise, including niche ones as they are an advantage here
Prepare your ID and tax papers (where necessary) prior to processing to avoid application delays.
Practice slowing down. Read each instruction twice before answering.
Research the details of the organization and projects you are applying for – they are not all the same and some are more likely to be interested in the data annotation skill or domain expertise.
For anyone considering which jobs and positions are still worth their time, Expertwoka's AI opportunities page shows jobs that are open now and what exactly they're looking for before dedicating time to one application.
