Coders: Smarter than AI? Prove It
The models shaping the future of AI are only as rigorous as the coders behind them. Apply your expertise where it matters, and get paid to do it.
As seen on
This is not busywork.
The most advanced code generation models still produce race conditions, ignore edge cases, hallucinate APIs, and write O(n³) solutions when linear time is trivial. You're the engineering filter that catches what compilers can't — one annotation at a time.
Three steps.
No overhead.
Apply & Qualify
Complete a short engineering assessment. We evaluate your ability to identify correctness bugs, reason about complexity, and write clean, idiomatic code. No résumé required.
Get Matched
Based on your preferred stack and assessment results, you're matched to projects in your areas of expertise. Systems programming, web backends, ML pipelines, mobile, infra — you choose what fits your background.
Work & Get Paid
Complete tasks on your own schedule. Each task has clear specifications, test cases, and a defined scope. Payment is per-task, processed weekly, starting at $50+/hour
What you'll actually do.
Write a prompt
Craft precise engineering prompts designed to probe the boundaries of model reasoning — not toy problems, but challenges that expose incorrect algorithms, unsafe memory access, and flawed system design decisions.
Review AI output
Evaluate whether the model's code actually works — catching off-by-one errors in loop logic, identifying race conditions in concurrent implementations, and flagging O(n²) solutions where a more efficient algorithm was straightforward.
Write the correct solution
Author a complete, production-quality implementation that demonstrates the correct approach. This becomes training signal for the next model generation.
Where models need you most.
These are the engineering domains where current AI code generation consistently produces dangerous output. Your expertise directly addresses the hardest open problems in coding AI.
Systems & Infrastructure
Evaluate AI reasoning about distributed systems, networking, operating systems, and infrastructure design. Verify claims about consensus protocols, storage engines, and scalability trade-offs.
Algorithms & Data Structures
Review model outputs on algorithm design, complexity analysis, and data structure selection. Catch incorrect Big-O claims, flawed dynamic programming formulations, and suboptimal data structure choices.
Security & Cryptography
Assess AI-generated code for security vulnerabilities, cryptographic misuse, and authentication flaws. Identify injection vectors, broken crypto implementations, and authorization bypass patterns.
Backend & API Design
Evaluate reasoning about API architecture, database design, caching strategies, and service communication. Identify N+1 queries, incorrect transaction isolation levels, and flawed idempotency implementations.
Frontend & Performance
Review model outputs on frontend architecture, rendering performance, state management, and accessibility. Verify claims about bundle optimization, hydration strategies, and browser API usage.
Paid to contributors
Expert annotators
Annotations completed
Built for people who think in systems.
CS Students
Upper-division and graduate CS students with strong foundations in algorithms, systems, and software engineering principles.
Software Engineers
Professional developers with production experience looking for flexible, intellectually demanding work outside their day jobs.
Staff & Principal Eng.
Senior engineers applying deep systems knowledge and architectural expertise to AI training data on their own schedule.
Open-Source Contributors
Maintainers and active contributors with demonstrated ability to write clean, well-tested, production-quality code.
Around the web
People love the work.
A few threads from contributors who’ve been at it for a while.
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r/DataAnnotationTech
u/NaToKy24
What I love most about DA: it's an actual meritocracy
What I absolutely love about working at DA is the meritocracy. The higher the quality of your work, the higher the reward.
Creating complex coding scenarios, doing deep analysis of models, and synthesizing results are all part of my daily routine, and I love it.
r/DataAnnotationTech
u/textartguy
Belated Milestone Post
Been working since March 2024. I honestly feel so lucky to have both found this job and to have been able to keep it for so long.
I thought I might make a few grand max at the start.
r/DataAnnotationTech
u/Sharp-Sherbert-4194
100K!
Hit 100k the other day! I do this full time. Not what I originally intended when I signed up, but I've managed so far.
I started as a generalist but I have coding work too.
r/DataAnnotationTech
u/Emelody_cellobabe
DA has seriously changed my life
This work has opened up so many opportunities for me and is now enabling me to work full-time independently.
I started as a generalist, then passed the coding eval and have more often than not had plenty of work.
r/DataAnnotationTech
u/E13AN0R
Just hit 75k!!
Started almost a year ago and have just hit this milestone :) I had just graduated from uni when I started doing this and it was a lifesaver whilst I was looking for graduate jobs.
I'm based in the UK and I have a Master's degree in physics so I do a mix of specialist stem, coding, and sometimes generalist projects.
r/DataAnnotationTech
u/LeatherScience633
DA saved me, and I wish I could say thanks
In just 2 months I have already paid off my debt that would have taken me around an year to pay back. I can also leave my extra jobs and actually focus on my passion instead.
Working for them has been the best thing to happen to me so far.
r/DataAnnotationTech
u/CharacterBlood1495
Hit the 10k mark in one month : )
I have earned 10k in a month (my first month started at the end of April). I needed this and will definitely continue working with them.
I plan to keep working and be able to pay for a masters maybe in the fall.
r/DataAnnotationTech
u/OhLemons
Broke 130k this month!
I love that I can switch between coding tasks and those with rubrics, and that the work is always changing, so it never gets boring.
The taxes hurt, but it is worth it to help support the services like free healthcare here in Canada.
r/DataAnnotationTech
u/paranormalisnormal
$40k - I Love You Data Annotation <3
Data Annotation has saved my ass financially and allowed me to help out my loved ones. Couldn't ask for a better job.
I've been working about 2-3 hours a day, 5 days a week, for just over 2 years.
r/DataAnnotationTech
u/PossibilityNo1696
200k Club
Treated DA as pretty much full time for the past 3 years and its been a god send for me.
I've saved a huge amount of money working from home, managed to work on a part time masters degree, and also been able to spend more time on myself.
r/DataAnnotationTech
u/Responsible-Fly-3808
My personal experience with DA [CODING]
In less than 2 months I've made a little over $20k, which honestly still feels surreal typing out.
A lot of it feels like real engineering/problem-solving work — debugging code, evaluating implementations, reasoning about edge cases.
r/DataAnnotationTech
u/MCSquareGlobe
Actually can help pay student debt now
This made living as a grad student actually affordable. In 2 weeks I just over doubled what I normally make.
Half of what I need to do in grad school is writing, so writing practice has been well needed.
r/DataAnnotationTech
u/physicsandwolves
100k club
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Thanks DAT, I've been able to live an awesome life because of this job. Traveled to 28 countries, built a wrap around deck for my mom, created a massive garden, and so much more!
You can do it too, keep up the good work people!
r/DataAnnotationTech
u/neverenoughpepper
Jumping on the Milestone bandwagon
It's been a long, almost 3 year journey. Coder, self taught, and the first year or so was really, really tough. But I have no words for how thankful I am for DA.
I've had some amazing jobs in my life, but none compare to the constant challenges and rewards of this one.
Frequently Asked Questions
Have questions? Here we answer the most common questions.
You'll work on tasks that help AI perform better, like reviewing responses, checking accuracy, refining prompts, and rating outputs. No coding or technical background needed.
Projects vary but commonly include reviewing AI-generated text, ranking responses, checking facts, labeling data, and reviewing content in specific subject areas. All focused on improving real production AI systems.
This is ideal for people with strong reasoning skills, attention to detail, and subject-matter expertise who want flexible, remote work with real impact. Researchers, students, professionals, and independent contributors who enjoy analytical work and want to contribute to advancing AI systems.
This is a flexible, task-based contractor role. You work remotely on your own schedule, focused on output quality rather than hours logged. There is no long-term commitment required, and you can work as much or as little as you choose.
Get ahead in a changing workforce.
No recruiters. No interviews. Just meaningful work and real compensation.