DataAnnotation — Production-Grade Review
Apply now /* Desktop only css */ @media screen and (min-device-width: 992px) { .navbar5_link-drop:hover .nav-drop-wrapper { display: block; } .navbar5_link-drop:hover .nav-drop-arrow { transform: rotate(180deg); } .nav-link-drop:hover p { color: #004cf0; } .nav-link-drop:hover .nav-square { background-color: #004cf0; } } .nav-link-drop.w--current p { color: #004cf0; } .nav-link-drop.w--current .nav-square { background-color: #004cf0; } .navbar5_link.w--current .navbar-link_dot{ background-color: #004cf0; border: #004cf0; } [data-wf--navbar--variant="dark"] .navbar5_link.w--current .navbar-link_dot{ background-color: white } .navbar5_component.is--move .navbar5_container { transform: translateY(-100%); } [data-nav-menu-open] { display: flex !important; } CODING
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.
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.
These are not toy problems. You're evaluating whether a model correctly implements concurrent data structures, verifying algorithmic complexity claims, auditing security-critical code paths, debugging broken component rendering logic, and assessing system design trade-offs. The work demands the same rigor as a senior-level code review.
Sourced from Dataannotation. Apply through our listing to get matched.
What we look for
- Complete a skills assessment aligned with your expertise
- Work remotely on a flexible schedule
- Strong written English; domain expertise required
How it works
Apply once and complete a short skills assessment. Once approved you are matched to projects that fit your background, set your own weekly hours, and are paid on a regular cycle for the work you complete.