Full-Stack Software Engineer for AI Code Evaluation

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. It helps contributors discover specialized projects, build a professional profile, and apply to opportunities that match their experience. Creating an OpenTrain account is free.

About AI Code Evaluation

AI training depends on people who can create strong examples, solve technical problems, and assess whether model-generated work is correct and useful. In software-focused projects, engineers help AI systems improve by reviewing code, testing implementations, identifying defects, and evaluating qualities such as performance, security, and maintainability.

• Remote work supporting the development of advanced AI systems

• Flexible, part-time project commitment

• Technical work focused on software development and code evaluation

The Role

OpenTrain is recruiting a Full-Stack Software Engineer for AI training work centered on software development, technical problem-solving, debugging, system architecture, and code evaluation. You will work across front-end and back-end systems, create and solve challenging engineering tasks, validate implementations, translate complete coding builds between languages, and review AI-generated solutions.

This is an entry-level classified opportunity with a requirement for strong professional experience developing production full-stack applications. The role is a part-time contractor position requiring less than 20 hours per week, with an hourly rate of $50 to $100 USD.

• Employment type: Contractor and part-time

• Time requirement: Less than 20 hours per week

• Pay: $50-$100 USD per hour

• Working language: English

• Availability: Remote opportunity across the listed eligible countries

What You’ll Do

You will contribute to software-engineering tasks used in AI training, working across unfamiliar repositories and complete application architectures. Your work may involve developing features, tracing failures through complex systems, and assessing implementations across multiple programming languages.

• Develop, modify, and debug front-end and back-end application components

• Implement user-facing features and the APIs, services, and data models behind them

• Trace requests and data across browsers, applications, APIs, services, databases, and external integrations

• Understand unfamiliar repositories and contribute to complete application architecture

• Diagnose failures involving application state, API contracts, authentication, persistence, networking, and deployment

• Create, solve, review, and validate software-engineering tasks for AI training

• Evaluate and improve code written in multiple programming languages

• Review implementations for correctness, completeness, performance, security, and maintainability

• Translate complete coding builds between programming languages

Required Qualifications

Strong professional experience developing production full-stack applications is required. You should be comfortable working across front-end and back-end engineering and analyzing how application components work together in production environments.

• Production full-stack application development across front-end and back-end systems

• Hands-on experience with both front-end and back-end engineering

• Production experience with multiple programming languages

• Strong knowledge of browser applications, APIs, application state, databases, and service integration

• Experience understanding and contributing to complete software-system architecture

• Ability to work effectively in unfamiliar repositories and codebases

• Strong debugging and technical problem-solving skills

• Ability to evaluate code for correctness, performance, security, and maintainability across multiple programming languages

Helpful Technical Background

Experience with a range of full-stack and programming technologies can support the multi-language nature of this work. Familiarity with AI-generated code review is especially relevant when assessing software quality and validating technical solutions.

• Python

• React

• JavaScript

• Java

• Node.js

• Rust

• Go

• TypeScript

• Reviewing AI-generated code

• Assessing software security, performance, and maintainability

Build Your AI Training Career

AI training and data labeling are the human side of building artificial intelligence. Engineers, writers, analysts, and other specialists prepare and review examples that help moder…