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OpenTrain AIFor AI Companies

Java libGDX Game Developer For AI Training

Build and optimize 2D game features in Java/libGDX to generate training data for AI systems; remote contractor role, 20+ hrs/week, $20–$120/hr. Ideal for entry-level developers with libGDX experience and a small-games portfolio.

OpenTrain AI

Coding Software

100% Remote Hourly · $20–$120/hr

$20–$120/hr

Compensation

Worldwide

Eligibility

Entry

Experience

Jun 30, 2026

Posted

Open worldwide

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About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. The platform helps freelancers consolidate proof-of-work, discover projects that fit their skills, and develop a durable portfolio working on real AI training tasks.

Working with OpenTrain connects you to projects across the industry while you build demonstrable experience shaping how AI models learn.

About AI training and why it matters

AI training (also called data labeling or human feedback work) is the human side of building modern AI: people prepare, test, and curate examples that teach models how to reason, respond, and act. Contributors work across text, audio, image, code, and interactive environments.

This role puts game development at the center of that process: by building reliable 2D interactions you’ll help produce high-quality data that directly influences how next‑generation AI systems behave.

The role

OpenTrain is recruiting an AI Training Game Developer (Java / libGDX) to develop and optimize simple 2D game features used to generate training data. You will work as a remote contractor for OpenTrain on part-time hours and collaborate closely with AI specialists to design interactions that produce reliable, high-value training examples.

This is an entry-level friendly role that emphasizes practical libGDX experience, clear technical documentation, and the ability to work in a distributed team.

What you'll do

  • Develop, maintain, and optimize 2D game features using Java and libGDX.
  • Implement core mechanics: game loops, sprite management, input handling, and basic 2D physics.
  • Collaborate with AI specialists to design interactions that generate high-quality training data.
  • Troubleshoot and debug game modules to ensure performance and reliability.
  • Participate in code reviews and help improve internal coding standards.
  • Document technical processes and workflows so cross-functional teams can use your modules.
  • Communicate regularly with the team, provide progress updates, and incorporate feedback.

Requirements

  • Basic knowledge of Java and object-oriented programming principles.
  • Hands-on experience with libGDX from coursework, personal projects, or prototypes.
  • Understanding of game development fundamentals: game loops, sprites, and input management.
  • Strong written and verbal communication skills for technical documentation.
  • Ability to work collaboratively in a fully remote team.
  • Demonstrated interest and initiative in building games or interactive applications.
  • English language proficiency (job materials and team communication in English).
  • Availability for 20+ hours per week as a contractor.

Helpful background (not required)

A small portfolio of playable demos or GitHub projects will make your application stronger.

Familiarity with vectors, collision detection, or basic 2D physics and experience using Git for version control are advantages.

Compensation & logistics

This contract, part-time role pays between $20 and $120 USD per hour (PAY_PER_HOUR). Exact rate within that range will depend on experience and agreement with OpenTrain.

The position is remote and open to candidates worldwide. Work is expected to be delivered collaboratively and documented for cross-team use.

How to apply

Create or update your OpenTrain profile and apply with links to your portfolio, GitHub, or playable demos. Highlight relevant libGDX projects and any examples of 2D mechanics you implemented.

Be prepared to describe your role in past projects, share code samples or demos, and explain how you approached debugging and performance optimization.