• Create and solve realistic full-stack tasks involving user-facing features and APIs. • Trace requests and data across browsers and back-end services to judge whether an AI implementation works correctly.
Responsibilities:
— Design and solve realistic full-stack tasks that include user-facing features and APIs.
— Trace requests and data flow across browsers and back-end services to evaluate AI implementations.
— Write professional reference solutions and validate code for both front-end and back-end systems.
— Review AI-generated code focusing on security, performance, and maintainability, providing explanations for improvements.
Requirements:
— Strong professional experience in building production full-stack applications using multiple programming languages.
— Deep knowledge of full-stack systems including browser applications, APIs, application state, databases, service integration, architecture, and debugging.
— Professional fluency in English.
— Experience contributing to complete software-system architecture, working with unfamiliar codebases, and solving complex debugging problems.
— No prior AI experience required; experience reviewing AI-generated code for security, performance, and maintainability is a plus.
Benefits:
— Compensation of $50–$100 per hour equivalent, paid per accepted task.
— Part-time contract work under 20 hours per week with flexible scheduling.
— Fully remote position based in the United States.
Additional Information:
— Application process includes a short application on the hiring platform and a conversational AI interview with technical questions and a coding challenge.
— OpenTrain AI connects professionals with paid, part-time AI training work to improve AI systems currently being developed.
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Понятные задачи
Задачи подробно описаны: создание и решение реалистичных full-stack задач, трассировка запросов и данных, написание эталонных решений и проверка кода.
Из объявления
Work on AI code evaluation on your own schedule, using your full-stack engineering judgment to create, review and validate software tasks. … • Create and solve realistic full-stack tasks involving user-facing features and APIs … • Trace requests and data across browsers and back-end services to judge whether an AI implementation works correctly