Research Engineer

What you'll do

• Build world-generation pipelines, data-efficient training methods, and inference-time optimization for real-time generation.
• Develop distributed multi-agent orchestration for world synthesis, including terrain, assets, and behavior trees.
• Work on reinforcement learning pipelines and agentic code-generation or diffusion tools for simulated environments.

What they ask for

• Strong software fundamentals and ability to work across production systems and research.
• Experience building or training large multimodal or agentic systems.
• Familiarity with distributed training, data curation, or large-scale vision/3D pipelines.

Nice to have

• Experience with generative vision, world models, or RL systems.
• Experience with diffusion or generative vision models, robotics, multi-agent systems, simulation-based RL, game engines, or 3D simulation frameworks.

Pay

$200,000 – $350,000 USD base salary; $165,750- $353,250 equity and benefits; $200K – $350K USD; 0.5% – 1.5%

Tools

diffusion, Reinforcement learning, game engines, 3D simulation frameworks

AI focus

Applied AI for 3D world and game generation, including multimodal and agentic systems, distributed orchestration, reinforcement learning, diffusion-based tooling, and real-time inference optimization.