The work
You will help create and improve datasets used to train and test large language models. The work applies production software engineering judgment to code examples, AI-generated solutions, and automated checks.
You will work across backend services, data pipelines, machine learning infrastructure, and full-stack applications. Your evaluations will cover code quality, architecture, debugging, scalability, reliability, and practical use in real engineering settings.
- Curate Python code examples for backend services, data pipelines, and machine learning infrastructure.
- Write and correct solutions in Python, JavaScript, ReactJS, C or C++, Java, Rust, and Go.
- Review AI-generated code for architecture, implementation quality, debugging, scalability, and reliability.
- Create Python agents and automated verification tools that test software engineering solutions and find recurring error patterns.
- Assess AI capabilities across prototyping, architecture design, API design, production implementation, launch, experimentation, monitoring, and operational maintenance.
- Work with cross-functional teams to improve AI coding solutions against industry performance benchmarks.
What it pays and takes
Pay details are not provided in this listing. This is an individual contractor engagement with a flexible part-time commitment and an initial duration of one month, with possible extensions based on performance and fit.
- Pay: Not specified.
- Time: 20 or more hours per week.
- Location: Open to candidates based in the United States.
- Engagement: Individual contractor and part-time.
- Experience: At least three years of software engineering experience.
- Technical skills: Strong Python expertise, including production frameworks and tooling, plus experience building full-stack applications and deploying scalable software.
- Engineering judgment: Understanding of software architecture, design, development, debugging, and code review.
- Communication: Ability to give clear, structured written and spoken reasons for technical evaluations.
- Helpful background: Experience with production systems in high-scale engineering environments and a strong computer science foundation. Practical engineering skill matters more than a particular school or employer background.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training work is the human side of building artificial intelligence. People prepare examples, review model outputs, and test software so AI systems can produce more useful and reliable results; experienced engineers are needed when the work calls for production judgment and specialized technical knowledge.