AI Researcher
RadixArk
AI Researcher
RadixArk
Open-source AI infrastructure for large-scale inference
We’re looking for researchers and engineers who love training the best AI models. You’ll work on the full training stack, from data and recipes to post-training, RL, and evaluation, alongside a small, high-caliber team building at the frontier of AI systems.
Pre-training, mid-training, and post-training of large models
Reinforcement learning, reasoning, and reward modeling
Data, evaluation, and the research behind making models measurably better
Have a track record of research or engineering on large-model training
Care about shipping results, not just publishing them
Are curious, direct, and comfortable with ambiguity
RadixArk develops large-scale AI infrastructure for training and deploying models. Its core offering is the open-source SGLang engine that accelerates model inference, complemented by Miles, an open-source framework tailored for large-scale reinforcement learning and post-training tasks. The company provides managed infrastructure and production-grade tooling for model inference and post-training, with additional commercial products built on top of its open-source foundations. Revenue comes from managed hosting services and other paid offerings. Unlike many competitors, RadixArk pursues an open-core model to keep its core technology open and accessible to researchers, startups, and enterprises while monetizing via hosted services and premium tools. The goal is to democratize frontier AI infrastructure, reducing duplicated effort and enabling the AI community to train, deploy, and operate advanced models more efficiently and affordably.
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