Game Developer (Godot Expert)

You will review Godot game projects, source materials, and AI model outputs against project guidelines. Your feedback will help improve how AI systems understand and produce game development work.

The role focuses on clear technical judgment and consistent review across repeated tasks.

• Review project materials and model outputs using project rubrics.
• Write clear feedback that explains your technical judgments.
• Assess Godot gameplay systems and technical workflow instructions.
• Maintain consistent quality across review tasks.

What it pays and takes

This is remote contractor work with flexible weekly hours over a 1 to 3 month project period. Previous AI training experience is not required.

• Pay: $70 to $130 per hour.
• Schedule: Flexible weekly hours over 1 to 3 months.
• Location: Open to candidates in the countries listed for this role.
• Language: English proficiency at B2 level or higher.
• Strong hands-on professional experience with the Godot game engine.
• Experience with GDScript or C# programming.
• Knowledge of 2D and 3D game development, scenes, nodes, and animations.
• Ability to develop, debug, and optimize gameplay systems.
• Access to Godot and the ability to record your screen while completing tasks.
• Ability to explain technical workflows clearly.
• Helpful: A portfolio of Godot projects, professional game development experience, or a relevant master's degree or PhD.
• Helpful: Experience with multiplayer games, game physics, UI and UX development, data annotation, RLHF, or AI model evaluation.

How it works

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 5 screening questions.

About AI training work

AI training is the human work behind systems that learn from examples, reviews, and written feedback. People with strong technical experience help evaluate model outputs and explain specialized workflows so AI systems can improve.