- 经验
- 任何
- 薪水
- 每小时 50 至 100 美元
- 职位空缺
- 1
- 发布
- 2天前
- 工作模式
- 在家办公
- 学历
- 学士学位
- 合格
- Applicants must be able to work independently as contractors and be based in the United States, Canada, the United Kingdom, Ireland, Australia, or New Zealand.
- 恢复
- 需要申请
职位描述
Role overview
This role is for an experienced Manual QA Engineer who will contribute to AI training work within a large engineering community focused on improving machine intelligence. The position blends coding, quality evaluation, and written feedback to help refine systems that can learn and improve over time.
Work may include developing and solving programming challenges, building feature-rich applications, and drawing conclusions from data analysis and visualization tasks. Some contributors use this as a supplemental role alongside another full-time job, while others dedicate it as their main work, selecting projects and hours that fit their own availability.
How the process works
After creating an account, candidates complete a short assessment that acts as the screening step. Successful applicants receive confirmation by email, after which paid tasks become available on the platform.
What the work involves
- Create and solve a variety of coding problems used to train AI systems, with a focus on Android-related development.
- Produce clean code examples along with clear, detailed explanations.
- Review AI-generated code for correctness, efficiency, and readability.
- Share feedback that helps improve the next generation of AI models.
Compensation and engagement terms
This is an independent contractor opportunity. Payment is made through PayPal, and PayPal handles any currency conversion from USD. There is no request for payment from candidates at any stage.
Hourly projects start at $50–$100+ per hour, and some assignments may pay more depending on the work.
Availability and location
The role is available only to candidates located in the United States, Canada, the United Kingdom, Ireland, Australia, and New Zealand. Applicants outside these countries will not currently see assessments or work on the platform.
Additional information
The platform supports flexible scheduling and allows contributors to work on their own computer from home, choosing projects and timing that suit them best.
This opportunity is associated with a community of more than 100,000 professionals across front-end, back-end, full-stack, machine learning, and related engineering disciplines.
#SWE