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# Jr Game Developer Panda3D - Remote

- **Company:** YO AI Labs
- **Location:** Amsterdam, Netherlands (Remote available)
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Code Review, Video Game Development, Game Engine, Github, Python (Programming Language), Open Source Technology, Software Organization, Computer Gaming
- **Published:** July 15, 2026
- **Apply:** https://www.adzuna.nl/details/5792114678

## About the Role

* Solid hands-on experience with Python programming, especially in game development contexts.
 * Strong understanding of the Panda3D engine and its practical application in creating interactive 3D environments.
 * Familiarity with C++ and its integration within game engines.
 * Proficient in using GitHub for version control, code reviews, and collaboration.
 * Ability to communicate complex technical concepts clearly and effectively.
 * Meticulous attention to detail and problem-solving mindset.
 * Self-motivated and comfortable working independently in a remote setting.

Preferred Qualifications:

 * Previous experience contributing to open-source projects or AI-related initiatives.
 * Knowledge of modern software development practices and pipelines in game development.

## Description

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required - your domain knowledge is what matters., * Leverage your proficiency in Python and C++ to provide insights and feedback on interactive game development tasks.

 * Utilize the Panda3D engine to review, critique, and suggest improvements on code samples and game logic.
 * Contribute domain-specific examples to help enhance AI understanding of modern game development workflows.
 * Analyze and address practical challenges in game rendering, asset management, and gameplay mechanics.
 * Document and explain decision-making processes in a clear, concise manner for AI training purposes.
 * Collaborate with a distributed team to deliver high-quality, real-world input that shapes future AI technologies.
 * Participate in iterative feedback cycles to continuously improve AI learning outcomes.


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