$50-75/hrAs published by the platform.
This contract role centers on building and improving the high-performance C systems that move and check data for AI model training and evaluation. It suits senior engineers with several years of production C experience who can also work on backend and tooling layers.
$50-75/hr
Pay as published by the platform. It is not a guarantee of income or hours.
The platform has not published which countries are eligible for this job.
You apply on Alignerr, Labelbox's expert network: create a profile, complete an AI-led interview and skills assessment, then get matched to projects in your field.
Official posting: https://www.alignerr.com/jobs/100d3f6b-dc04-49cc-a1af-b2027b394a8c
Last checked on October 8, 2026.
This role involves designing and optimizing Python-based backend systems for data annotation, validation, and AI model training infrastructure. The position requires a senior full-stack engineer to build high-performance data pipelines, asynchronous task queues, and evaluation systems used by leading AI labs.
This remote contract role asks experienced full-stack developers to review and evaluate code and system designs produced by AI models. The work also includes building tooling for data annotation and quality control, done asynchronously on a flexible schedule. It suits engineers with several years of production experience who can give precise technical feedback.
This remote study asks practicing software engineers to review programming tasks and the evaluation harnesses built to test AI agents on them. You will check whether the tasks, test cases and environment structure reflect realistic software engineering work. It suits engineers with solid experience building, testing and reviewing complex systems.
Posted October 2, 2026
You will evaluate the quality and correctness of AI-assisted software development traces used to train and assess models at a leading AI laboratory. You must judge the accuracy of coding sessions, the consistency of workflows, and the quality of reasoning, then provide structured written feedback according to an evaluation grid.
Posted August 28, 2026
Backend engineers will evaluate how AI models reason about system design, data modeling, and API contracts, identifying failures like race conditions and N+1 queries that only surface under real load. The role involves stress-testing model-generated backend code and writing correct solutions when models fall short, with explicit attention to scaling and consistency trade-offs.
A Full Stack Engineer working with frontier AI models to evaluate their ability to build complete applications across frontend, API, and database layers. You will trace features through the entire stack to identify where models fail, write corrected versions when needed, and provide detailed explanations that serve as training data for improving future model outputs.
