The work
You will evaluate AI-generated Java code, architectural solutions, and technical explanations. Your reviews will focus on correctness, clarity, prompt adherence, technical reasoning, and production-quality engineering practices.
You will also create training material that helps improve AI systems, including reference implementations, model answers, prompts, reasoning steps, and comparative feedback.
- Review AI-generated Java code, architecture, and explanations.
- Find logic, performance, and design problems in Java responses.
- Rate and compare AI answers for correctness and reasoning quality.
- Write reference implementations, model answers, and structured reasoning.
- Create prompts and responses for AI training content.
- Review work involving Spring Boot, REST APIs, microservices, distributed systems, and performance optimization.
What it pays and takes
This is a part-time contractor role for an expert Java engineer. Previous AI training, data annotation, or AI-generated content evaluation experience is helpful but not required.
- Pay: $55 per hour.
- Time: 20+ hours per week.
- Work arrangement: Remote contractor role.
- Open to candidates in Bangladesh, Bhutan, Brazil, Cambodia, Germany, India, Indonesia, Malaysia, Nepal, Pakistan, Singapore, Sri Lanka, Thailand, the Philippines, the United States, Timor-Leste, and Vietnam.
- Language: Professional fluency in English and clear written communication.
- Experience: Strong professional Java engineering background with production experience.
- Technical knowledge: Core Java, concurrency, the Java Collections Framework, Spring or Spring Boot, REST APIs, and microservice architectures.
- Work skills: Careful code review, systematic debugging, performance analysis, and structured technical feedback.
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 generate and understand code, text, images, and other content. Contributors review model outputs, write examples, and give feedback so AI systems become more accurate and useful; experienced specialists are valued for applying real professional judgment.