Senior Backend Engineer (Python/FastAPI) AI Evaluation

You will help evaluate and improve code used to train and benchmark AI models. The work covers backend, infrastructure, and systems software, with a focus on correctness, performance, reliability, and clear technical reasoning.

• Curate code examples and create solutions in Python, C/C++, Rust, Go, Java, and JavaScript, including ReactJS.
• Correct and refine AI-generated code for accuracy, efficiency, scalability, performance, and reliability.
• Build software checks that test proposed solutions and help identify recurring errors.
• Evaluate coding capabilities across prototyping, architecture and API design, implementation, launch, experimentation, monitoring, and maintenance.
• Work with research and other teams to assess solutions against software performance benchmarks.

What it pays and takes

• Pay: Not provided.
• Schedule: Flexible, with a commitment of 20 or more hours per week.
• Location: Open to candidates in the United States.
• Engagement: Contractor role, initially one month, with potential extensions based on performance and fit.
• Requires at least three years of software engineering experience and strong skills in systems programming, infrastructure, or backend development.
• Requires particular familiarity with Python, C/C++, Rust, or Go, plus experience building and deploying scalable production software.
• You should understand software architecture, design, development, debugging, and code review, and be able to explain technical evaluations clearly in writing and conversation.
• A strong computer science foundation and experience building production systems at a high-scale engineering organization are helpful. Engineering skill and relevant experience matter more than a particular school or employer background.
• Professional fluency in English is required.

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 and review examples that help models learn. Experienced software engineers are needed to assess code and technical solutions carefully, helping produce more reliable training data and AI coding systems.