Senior Backend Engineer (Python/FastAPI) AI Code Evaluation

Create and improve datasets used to train and assess large language models. You will use software engineering judgment to review code examples, model-generated solutions, and automated checks.

• Curate Python code examples for backend services, data pipelines, and machine learning infrastructure.
• Write and correct solutions in Python, JavaScript and ReactJS, C or C++, Java, Rust, and Go.
• Assess AI-generated code for architecture, implementation quality, debugging, scalability, and reliability.
• Build Python agents and automated checks that test software solutions and identify recurring errors.
• Evaluate model capabilities across prototyping, architecture and API design, production implementation, launch, experimentation, monitoring, and operational maintenance.
• Work with cross-functional teams to improve AI coding solutions against industry performance benchmarks.

Hours, location, and qualifications

• Location: You must be based in the United States.
• Commitment: 20 or more hours per week.
• Engagement: Individual contractor role, initially one month, with possible extensions based on performance and fit.
• Required experience: At least three years in software engineering, with strong Python skills, including production frameworks and tools.
• You should have experience building full-stack applications and deploying scalable software, plus knowledge of software architecture, design, development, debugging, and code review.
• You must be able to explain technical evaluations clearly in writing and conversation.
• Experience building production systems in high-scale engineering environments and a strong computer science foundation are helpful.

How to apply

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work uses examples prepared and reviewed by people to teach and evaluate AI models. Software engineers bring practical expertise to judging code quality and model performance on real engineering tasks.