AI Engineer

R2D Games; Fatih; On-site; Full time

Job summary

A game generation company is seeking an individual to research and prototype LLM-based game generation pipelines. The ideal candidate will have hands-on experience with LLMs and strong PyTorch knowledge. Responsibilities include improving game generation quality and building automated testing infrastructure. This role offers a dynamic environment where input will shape next-gen game development, ideal for those passionate about shipping fast prototypes and packaging them into demos.

Qualifications

• Hands-on experience with LLMs in code generation and tool-calling.
• Strong knowledge of PyTorch or equivalent deep learning frameworks.
• Solid foundations in NLP and generative methods are essential.

Responsibilities

• Research and prototype game generation pipelines with LLMs.
• Combine LLMs with classic NLP techniques to improve quality.
• Build automated testing and evaluation infrastructure.

Skills

Experience with LLMs

Strong PyTorch knowledge

Solid foundations in NLP

Production-minded engineering

Fast prototyping

Tools

Git

Docker

Cloud

CI/CD

Job description

Game Generation Factory is a next-gen platform that turns ideas into playable AI-orchestrated “game studio” workflow. We’re building a product where creation feels fast, intuitive, and empowering—so more people can ship games without friction.

Responsibilities

• Research and prototype LLM-based game generation pipelines (prompting, planning, editing)
• Combine LLMs with classic NLP techniques to improve quality (templates, rule-based checks, post-processing)
• Apply and improve state-of-the-art approaches for code generation and code editing
• Build automated testing + evaluation infrastructure (playability, consistency, determinism, cost/latency)
• Reduce generation costs (caching, delta edits, batching, retries, guardrails)
• Work iteratively with the product team: metrics → hypothesis → experiment → shipping

Requirements

• Hands-on experience with LLMs (code gen, tool-calling, agents, evals)
• Strong PyTorch knowledge (or equivalent deep learning experience)
• Solid foundations in NLP + generative methods
• Production-minded engineering: Git, Docker, Cloud, CI/CD
• Habit of shipping fast prototypes and packaging them into demos