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Magics mission is to build safe AGI that accelerates humanitys progress on the worlds most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal.
As a Software Engineer working on our post-training data infrastructure, you will write efficient and robust data pipelines and collaborate with research and Applied teams to devise strategies for gathering and maintaining specific, diverse datasets at scale.
Magic values quick learning and grit, alongside skill and experience. We strive to be a place where high-potential individuals can do their best work.
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