Junior Python Game Developer (Panda3D) AI Trainer

About OpenTrain

OpenTrain is the #1 platform for people who build careers in AI training and data labeling. We help contributors find projects, consolidate work across platforms, and build a unified portfolio that showcases the AI training tasks they perform.

We focus on real, applied contributions that shape how AI systems learn — from code and game logic to transcriptions and image labels — while supporting flexible, remote work that fits a variety of schedules and skill levels.

Why AI training matters

AI systems learn from human examples and feedback. Contributors who annotate, review, and evaluate real artifacts—code, gameplay, transcripts, images—directly influence how models behave in practical settings.

This role lets you apply game-development expertise to teach AI about interactive systems, rendering, asset workflows, and gameplay mechanics, helping models better understand real-world development practices.

The role

We are looking for an entry-level Junior Python Game Developer with strong Panda3D experience to contribute to ongoing AI training tasks. You will provide high-quality code reviews, example code, and explanatory notes that help AI systems learn from real development decisions.

This is a remote contractor role, approximately 20+ hours per week, with pay between $20 and $70 USD per hour depending on experience and task complexity. The project is ongoing and supports long-term contributions.

• Employment type: Contractor, Part-time
• Workload: ~20 hours/week
• Pay: $20–$70 USD per hour
• Location: Remote, worldwide
• Duration: Ongoing project

What you'll do

Provide concrete, developer-focused input that AI systems can learn from: code critiques, design notes, and annotated examples built with Panda3D.

Work with a distributed team in iterative feedback cycles to refine prompts, evaluation rubrics, and example datasets that capture best practices and common pitfalls in game development.

• Review and suggest improvements for Python and C++ code samples that use Panda3D.
• Write clear, short documentation explaining implementation choices for AI training use.
• Contribute domain-specific examples covering rendering, asset management, and gameplay mechanics.
• Participate in evaluation and rating tasks to judge code quality and correctness.

Requirements

Candidates must have hands-on experience with Python in game development and a strong, practical understanding of the Panda3D engine. Familiarity with C++ integration in game engines and regular use of GitHub for collaboration are required.

You must be able to explain technical decisions clearly and document processes so they can be used as training examples for AI systems.

• Solid Python programming experience, especially for game projects
• Practical experience with Panda3D and 3D interactive environments
• Familiarity with C++ and engine integration
• Comfortable using GitHub for version control and code review
• Strong written communication and attention to detail
• Self-motivated, able to work independently in a remote setting
• Applicants must describe their Panda3D experience and provide links or examples of relevant projects

Helpful background

Open-source contributions, prior AI-related initiatives, or experience with modern game development pipelines (asset pipelines, build systems, CI) are beneficial but not required. These experiences help you produce clearer, higher-value examples for AI training.

• Open-source game or tool contributions
• Familiarity with build systems, CI, or asset pipelines
• Previous involvement in evaluation/rating tasks for software or AI

How the project works

Tasks will include reviewing submitted code, creating short annotated examples, and answering targeted evaluation questions about implementation choices. Work is organized into iterative batches with clear instructions and examples.

You will submit work via GitHub or the project’s annotation platform and participate in feedback cycles to refine annotations and examples. Quality and clarity are the primary measures of success.

• Deliverables: code reviews, annotated samples, short written explanations
• Tools: GitHub and the project’s annotation/review software
• Workflow: batch tasks with iterative feedback and quality checks

How to apply

To apply, send a brief description of your Panda3D experience, links or examples of relevant projects, and a short note about your availability for ~20 hours/week. Include any open-source contributions or sample code you can share.

We evaluate candidates on demonstrated Panda3D experience, clarity of communication, and the quality of examples provided. Successful applicants will be invited to complete a short evaluation task.

• Required in your application: description of Panda3D experience and links/examples
• Language: English required
• Expected next step: short paid evaluation task to assess fit