r/AiTraining_Annotation

Over the years, many lists of AI training and data annotation companies have circulated on Reddit, but a lot of them are now outdated or mix very different types of platforms. I put together an updated 2026 list covering AI training, data annotation, LLM feedback, and related AI work
Full list, reviews and open jobs here: https://www.aitrainingjobs.it/best-ai-training-data-annotation-companies-updated-2026/ 

Data Annotation. Tech
Platform specialized in AI response comparison, evaluation, and human feedback tasks used to improve large language models, with a strong focus on reasoning-heavy work.

TELUS International AI
Global AI services provider offering search evaluation, AI training, and linguistic data work for major technology companies, including former Lionbridge AI programs.

Scale AI
Enterprise-focused AI data platform supporting advanced machine learning systems through large-scale data annotation, validation, and model evaluation workflows.

Ethos AI

AI-powered expert network connecting experienced professionals with AI training, consulting, and research projects across fields such as law, finance, medicine, and engineering. The page currently reports advertised rates of $70–$225/hour.

Rise Data Labs
AI training and data annotation company focused on model evaluation, RLHF workflows, and high-quality data production, often involving more advanced and structured AI tasks.

Appen
One of the longest-running AI data annotation companies, offering a wide range of remote AI training, language, and data labeling projects.

Merco
AI-focused talent marketplace connecting vetted professionals with project-based AI, data, and engineering roles, closer to a talent network than a task platform.

Micro1
AI workforce and staffing platform offering higher-paying AI training and domain-specific roles, often requiring subject-matter expertise.

SuperAnnotate
AI data annotation platform offering tools and projects for image, video, text, and LLM-related annotation tasks, widely used in computer vision workflows.

TransPerfect
Global language and localization company working on large-scale AI training and multilingual data annotation projects for enterprise clients.

Gloz
AI training platform focused on language-based data annotation and LLM evaluation through structured text review and human feedback tasks.

Mindrift
AI training and data services platform focused on LLM evaluation and structured human feedback to improve model quality and alignment.

Braintrust
Decentralized talent network connecting vetted professionals with AI, engineering, and data-related projects through client-driven work.

iMerit
Enterprise-level AI data services company specializing in high-quality data annotation and model evaluation for complex use cases such as healthcare and NLP.

Outlier
AI training platform focused on reviewing and evaluating AI-generated responses through structured LLM feedback tasks, with relatively easy onboarding.

Invisible Technologies
AI operations and data services company offering structured, team-based AI training and data work for enterprise clients.

OneForma
Global AI training and crowdsourcing platform offering data annotation, transcription, translation, and linguistic evaluation tasks, widely used for multilingual projects.

Welocalize
Localization and language services company offering AI training, search evaluation, and multilingual data annotation work.

LXT AI
Global AI data annotation and training company focused on language, speech, and localization projects for enterprise clients.

Lionbridge
Formerly a major AI training and search evaluation company; most AI programs are now operated under TELUS International AI.

Innodata
Enterprise-level AI data services company specializing in large-scale data annotation and structured AI training projects.

Alignerr
AI training platform focused on cognitive labeling, decision evaluation, and ethical AI alignment tasks emphasizing human reasoning.

Abaka AI
AI training and evaluation platform offering contract work focused on reasoning-based annotation and human feedback, often cited for higher pay.

Stellar AI
AI training and evaluation platform offering project-based annotation and quality assurance work with a strong focus on accuracy.

SME Careers
Platform connecting subject-matter experts with high-paying AI training, expert review, and model evaluation projects.

Cohere
Enterprise AI company focused on large language models, offering expert-level roles rather than open crowd-based annotation tasks.

Perplexity AI
AI-powered search and answer engine offering professional research, engineering, and quality roles related to AI systems.

xAI
AI research and product company focused on large language models and advanced reasoning systems, offering highly selective roles.

Toloka
Global crowdsourcing platform offering beginner-friendly AI training microtasks such as content evaluation and data labeling.

Prolific
Online research platform connecting participants with paid academic and industry studies used for AI training and human feedback.

Remotasks
AI training platform focused on image, video, and LiDAR annotation for computer vision systems, with structured training programs.

CloudFactory
Global data operations company providing human-in-the-loop AI services through managed teams and structured workflows.

Clickworker
Crowdsourcing platform offering basic microtasks such as text labeling, image tagging, and surveys used for AI data collection.

Surge AI
Premium AI data services company focused on RLHF and high-quality human feedback for advanced AI models, operating through selective contracts.

Handshake
Career and recruiting platform connecting students and early-career professionals with structured AI-related roles, including AI training support, data labeling, research assistance, and model evaluation positions.

RWS
Enterprise language, localization, and AI data services company working with global clients on large-scale AI training, linguistic data annotation, and model evaluation projects.

TaskVerse
Microtask-based platform offering occasional AI-related tasks such as data labeling, content review, and basic human feedback.

Uber AI Solutions
Task-based platform offering flexible AI-related work such as data labeling, content evaluation, and basic human feedback tasks

RemoExperts (Rex.zone)
Expert-focused AI training and evaluation platform connecting vetted professionals with high-value remote projects such as LLM evaluation, RLHF, domain-specific analysis, and advanced data annotation. RemoExperts emphasizes selective onboarding, expert-level contributions, and competitive pay rather than open microtask workflows.

Silencio AI
Audio data collection app where contributors earn by capturing and submitting real-world sound recordings to support speech AI and voice recognition model training.

Centific
Enterprise AI data solutions company delivering large-scale human-in-the-loop workflows, high-quality datasets, and AI data infrastructure for global clients (not a typical microtask platform).

Fratch
AI-powered freelance marketplace connecting experienced professionals with consulting, AI, IT, engineering, finance, and digital transformation projects. FRATCH primarily serves the DACH market and uses AI-driven CV matching to connect freelancers with enterprise clients, making it better suited to experienced specialists than entry-level data annotation work.

Labela
AI workforce platform specializing in healthcare and life science experts for frontier AI training and evaluation projects. Labela connects physicians, researchers, and other subject-matter experts with remote opportunities involving AI response evaluation, clinical reasoning, and scientific model improvement.

Turing
AI research and talent platform connecting software developers, researchers, data scientists, and subject-matter experts with projects involving AI training, coding, model evaluation, advanced reasoning, and reinforcement learning. It focuses primarily on skilled and expert-level work.

Workada
Remote AI training and data labeling platform connecting contributors with projects involving text, image, and content evaluation tasks, with flexible contract work and structured onboarding.

As the title says,on Ethos AI I am getting matches but have been unable to convert them into opportunities and work. The best I have gotten so far is waitlist and tbh I dont know if I should be excited for that or not.

Any technical nuance which I need to do to improve my odds because I am damn sure my profile is strong because algorithm is matching me

Thanks and Regards

Recently i have been working for Ethos Ai. This was quite nice and eventually i should have received my payout last week. In my dashboard it says that the payout has been transfered.

Up until now i did not receive anything and to make it even worse they now started off boarding me. Will i then also lose all evidence of the work that i have been doing.

Are there here people who have worked for them and did actually get paid or dit i get scammed?

What can i do in this situation?

I’ve been working for Mercor (someone they contract me out to) for a bit now and they are so strict with time and finishing most things in less than 45 minutes. It is an intense pace and takes a large cognitive load. There is a program that monitors your screen while you work and that is how your time is kept.

I start working for Ethos as an education expert tomorrow. They let you record your own hours. It seems more lax based on this alone.

What are people’s experiences?

Anyone here knows a legit job site that I can apply for AI annotation or any other AI related job work? Tia.

Recently got qualified for [Artifacts] Slides Eval campaign and i have completed the screener. Can anyone tell me how much time is allowed for each task? Is there any max time limit for each task?

we had an agent sitting at ~96% on the same eval set for months

green builds

model upgrades passed

prompt changes passed

meanwhile production incidents started looking like:

• users asking much longer multi-part questions
• new tool combinations the original dataset never covered
• policy changed but half the expected answers didn't
• new slang / weird phrasing from an audience we didn't have six months ago
• prompt injection through retrieved content
• agent using a newly-added tool in a way nobody anticipated

the model hadn't “beaten” the benchmark

the benchmark had stopped describing production

i think calling these things golden datasets makes people subconsciously treat them like they're supposed to be frozen forever

but if you continuously rewrite the set, you lose comparability too

so i'm leaning toward two layers

small frozen core

cases that represent fundamental behavior and basically never disappear

• auth boundaries
• permissions
• critical business rules
• known catastrophic failures
• canonical happy paths
• then a rolling regression set fed by production

something breaks in prod:

• sanitize it
• remove PII
• preserve the failure pattern
• turn it into a scenario
• tag the feature/failure class
• run it forever or until the behavior is intentionally retired

plus periodically cluster recent failures/traffic and look for entire categories your dataset doesn't represent

TestMu Agent Testing fits pretty naturally into this loop for us because it can generate larger scenario sets from the agent requirements and run them against the actual endpoint

for voice/phone, production recordings can also be analysed to expose failure patterns that can feed future regression coverage

but i definitely would not auto-promote every weird production interaction into "gold"

someone still has to decide:

• was this actually a failure?
• is it important enough to preserve?
• what behavior should we expect next time?

and every eval run needs ridiculous amounts of version metadata:

• agent
• model
• prompt
• tools
• dataset
• judge/evaluator

otherwise 94% last month vs 91% today can mean almost anything

a frozen benchmark tells you whether you changed

a rolling dataset tells you whether you still resemble reality

i think you need both

how often are people actually refreshing their agent eval datasets, and what makes a production failure worthy of entering the golden set?

Just finished my first month working with Ethos. A great legitimate platform with smooth pay. Highly recommend it!

I want to share this because I’m sure I’m not the only person who has gone through this.
I’m 23, from Argentina, and over the last few months I’ve been trying to find a way into the AI industry.
Not as an AI engineer. Not as a machine learning expert.
I was looking for entry-level opportunities where I could actually use my skills: AI evaluation, data annotation, content, training AI models, and similar work.
At first, I thought it would be relatively easy.
I use ChatGPT and Claude a lot. I have experience with marketing, social media and content creation, and I’ve spent a lot of time learning how AI tools work.
So I thought: why not try?
That was when the rabbit hole started.
I signed up for Outlier and Remotasks, but I kept running into redirects, unavailable projects and access problems. I would complete my profile, look for work, and then… nothing.
Then I tried Prolific.
That didn’t go very well either. At one point I couldn’t even properly access my account and got the message:
“PEC-GL-0003: User not found.”
Which was honestly pretty frustrating after spending time trying to get everything set up.
I also tried Claru.ai, Data2Sales AI, HumanSignal, YPAI, Kled.ai and Atlas Core.
Some of them didn’t have projects available. Some had registration or access issues. In other cases, I simply couldn’t get past the point of actually finding work.
And after doing this over and over, I started asking myself:
“Am I doing something wrong?”
Because online, you see people talking about AI jobs all the time.
You see posts saying things like:
“Earn money training AI.”
“Work remotely.”
“Become an AI trainer.”
It sounds incredibly accessible.
But when you actually try to do it, you discover that getting the opportunity can be the hardest part.
And then there was Mindrift.
That was the first platform where I actually managed to move forward.
It wasn’t some huge breakthrough where suddenly everything worked perfectly.
But it was enough to make me realize:
Maybe I can actually find a place in this industry.
The interesting part is that my background isn’t really technical.
I’m from Argentina.
My native language is Spanish.
My English is still something I’m working on. I can understand and communicate in English, but I’m definitely not at a native or advanced professional level yet.
And honestly, that has made this whole process more difficult.
A lot of the information, communities, documentation and opportunities are in English.
So now I’m at a point where I don’t want to keep randomly signing up for every AI platform I find.
I want to actually learn.
I want to understand what I’m doing and build skills that companies are looking for.
I’m interested in AI evaluation, LLMs, data annotation, prompt engineering, computer vision, dataset creation, Python and, of course, improving my English.
But I have a problem:
I don’t really know where I should start.
So I’m posting this hoping someone with more experience can point me in the right direction.
If you’ve worked in AI training, data annotation, AI evaluation or anything similar:
What would you recommend learning first?
Are there courses or certifications that are actually worth doing?
Are there communities where beginners can learn and ask questions?
Which platforms are genuinely worth trying in 2026?
And most importantly, what would you recommend to someone like me?
A 23-year-old from Argentina, native Spanish speaker, still improving his English, with experience in marketing and content, who wants to seriously get into AI.
I’m not looking for a shortcut anymore.
I just want to find the right path.
I’ve already tried a lot of doors.
Most of them didn’t open.
But one finally did.
Now I want to know what I should do with that opportunity.
If you’ve been through something similar, I’d really appreciate your advice.
I’m still at the beginning of this journey, but I don’t want to give up.
Maybe someone reading this was in the exact same position at some point.
If that’s you, I’d love to hear your story.
#AI #ArtificialIntelligence #AITraining #DataAnnotation #AIEvaluation #LLM #CareerInAI #RemoteWork #Argentina #LearnAI #Mindrift

Unlike traditional AI data annotation platforms, Ethos recruits domain experts to help train and evaluate advanced AI models.

Current opportunities include professionals with backgrounds in:

• Law
• Medicine
• Software Engineering
• Tax
• Private Equity
• Corporate Development / M&A
• Management Consulting
• Advisory & Strategy

Most projects involve reviewing AI outputs, improving responses, evaluating complex scenarios, or creating high-quality expert content rather than performing simple annotation tasks.

Compensation depends on the role and level of expertise, with many listings ranging from $80/hour to $225/hour for qualified professionals.

I put together a guide covering how the platform works, typical expert roles, requirements, and current pay ranges:

👉 https://www.aitrainingjobs.it/ethos-ai-training-expert-jobs-100-225-hour-remote-opportunities/

Disclosure: the page contains a referral link that helps support the site at no extra cost if you decide to apply.

A lot of people think AI training jobs will disappear soon.

From what I’ve seen, the opposite is happening — but with a catch.

Simple tasks are slowly decreasing, while more complex work (reasoning, evaluation, decision-making) is becoming more important.

So the jobs aren’t going away… they’re getting harder.

I wrote a breakdown of where things are heading (2026–2030):
https://www.aitrainingjobs.it/the-future-of-ai-training-jobs-2026-2030/

Hey everyone,

I’ve been working steadily in the AI training and annotation space since last October. I’ve been lucky enough to have consistent work for most of the year, the constant uncertainty of contract work and queue availability is starting to wear on me.

Recently, I worked with Micro1 and was promoted to a semi-long-term role (4 months with a major AI company). Having a a taste of a steady 9-to-5 was a refreshing change of pace from the typical task-queue grind you find on platforms like Mercor or Outlier.

My question for those of you who have been in this space for a while: Is there an actual career ladder here?

Specifically, I’d love to hear your thoughts on:

1. Transitioning to W-2 / Salaried roles: Has anyone successfully parlayed platform RLHF/annotation experience into internal FTE roles (like AI Operations, Model Evaluation, Data Quality Lead, or Prompt Engineering)?
2. Skill-up paths: What skills (e.g., Python, SQL, guideline design, red-teaming) actually made the biggest difference in getting hired directly by AI startups or labs?
3. Platform vs. Direct Hire: Is staying on contract platforms and trying to move up into reviewer/lead roles the main path, or should the goal always be applying directly to tech companies?

If you've managed to build a stable, long-term career out of AI training and evaluation, how did you make the jump? Appreciate y'all!

Not all platforms are for beginners.

There’s actually a clear progression:

• beginner → DataAnnotation, Remotasks, Appen
• intermediate → TELUS, OneForma
• advanced → Outlier, Micro1, Mercor

If you start from the wrong level, it just doesn’t work.

I wrote a quick breakdown here (no fluff):
https://www.aitrainingjobs.it/best-ai-training-platforms-for-beginners-vs-experts-2026/

Curious if others had the same experience.

Opened my Gmail tonight and while scrolling through the junk, found a contract offer from Mercor for $70/hour! It said that though I hadn’t applied for the role, it took my skills from other applications and matched me.

I’d finally done an AI interview with them Sunday night, not really expecting much. But to my delight and surprise, this came through today. I signed the contract, verified my ID, and am waiting on the background check. The project might be short term but at least I’ll have my foot in. I’ve done a one-time $30 task there in the past.

Any tips from current or former Mercor workers? I started to read the onboarding and it told me to log those hours while I went through it — shocking! I’m used to not being paid for training.

I hope everyone is having a blessed week.

I'm seeing a lot of their job opportunities were posted in March. Now I'm starting to wonder how many of these are even worth applying to. Has anyone worked on a project since March?

I have seen many people and myself getting rejected even for the simplest roles. And they always have the roles up for hiring.
At this point I think they are only collecting data from their Ai interviews.

I’m considering AI training work through SME.Careers and would appreciate hearing from anyone who has actually gone through their process.

I’m interested in:

-What was the onboarding process like?
-How long did it take from application/acceptance to actually receiving work?
-Was the training or qualification process straightforward?
-What type of AI training or subject-matter-expert work did you do?
-Was the workload consistent, or did projects come and go?
How was communication and support from the company?
-Were payment, rates, and payment timing handled as expected?
-Did the actual work match what was described during recruiting?

Overall, would you recommend working with them?

I’ve found general information about the company, but I’m specifically looking for firsthand experiences from people who have completed onboarding or worked on projects through SME.Careers.

Positive, negative, or mixed experiences are all welcome. I’m mainly trying to understand what the process and day-to-day work are actually like.