The Work
You will create realistic computer-based tasks for NetBeans and Java software development. You will prepare projects and dependencies, document the task clearly, record the workflow, and review each submission for completeness, realism, and clarity.
- Create practical and challenging NetBeans tasks based on software development workflows.
- Prepare workspaces, projects, JDKs, dependencies, and reference materials before recording.
- Document goals, prerequisites, steps, expected outcomes, project files, and relevant notes.
- Record important workflow steps and states clearly on your computer.
- Work with project setup, imports, coding, debugging, Maven or Gradle, testing, GUI builders, plugins, and build or runtime troubleshooting.
- Review recordings and documentation against project guidelines.
What It Pays and Takes
This is a remote, part-time contractor role for contributors in Bangladesh, India, and Pakistan. The work requires hands-on NetBeans experience and strong written English.
- Pay: $20 per hour.
- Schedule: 20 or more hours per week.
- Location: Open to candidates in Bangladesh, India, and Pakistan.
- Language: Strong written English.
- Experience: Hands-on experience with NetBeans for Java development, project setup, debugging, Maven or Gradle workflows, GUI building, testing, or related software development tasks.
- Knowledge: NetBeans projects, packages, JDK configuration, run and debug workflows, build tools, plugins, code navigation, and output or error panels.
- Technical ability: Manage files, open projects, configure JDKs, install dependencies, and record computer workflows.
- Work style: Design realistic tasks, follow detailed instructions, work independently, explain technical workflows clearly, and maintain consistent quality.
- Useful experience: Java, backend development, quality assurance, GitHub, technical writing, coding, or teaching.
How It Works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI Training Work
AI training is the human work behind systems that learn from examples, including software tasks, written instructions, and evaluations. People with practical technical experience help make those examples accurate, realistic, and useful for improving AI systems.