Research Engineer
$200,000–$350,000 year
On-site · San Francisco, California, United States
Job Summary
You will work at the intersection of applied AI and large-scale systems, focusing on world generation pipelines, data-efficient training methods, and inference-time optimization for real-time generation. Responsibilities include developing distributed multi-agent orchestration systems for world synthesis, reinforcement learning pipelines for adaptive game generation, and agentic codegen tooling. Ideal candidates have a strong software background, experience with multimodal systems, and familiarity with 3D pipelines. The position offers a competitive compensation package with salary and equity, along with visa sponsorship and relocation support.
Required Qualifications
- Strong software fundamentals
- Experience building or training large multimodal or agentic systems
- Familiarity with distributed training, data curation, or large-scale vision/3D pipelines at scale
Desired Qualifications
- Experience training or fine-tuning diffusion or other generative vision models
- Prior work in robotics, multi-agent systems, or simulation-based RL
- Familiarity with game engines or 3D simulation frameworks as experimental testbeds
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