Make intelligence open and accessible to all. Backed by Battery, Lightspeed and Sequoia.
About the role
Bridge the gap between research and production by turning cutting-edge algorithms into scalable training systems. You will design and optimize the core infrastructure behind frontier AI models — from reinforcement learning training loops and distributed GPU training to massive-scale data pipelines. Our systems train models across thousands of GPUs and process petabyte-scale datasets. We care deeply about numerical stability, throughput, and reproducibility.
More about this role
Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all.
Bridge the gap between research and production by turning cutting-edge algorithms into scalable training systems. You will design and optimize the core infrastructure behind frontier AI models — from reinforcement learning training loops and distributed GPU training to massive-scale data pipelines.
Our systems train models across thousands of GPUs and process petabyte-scale datasets. We care deeply about numerical stability, throughput, and reproducibility.
This team owns and evolves the core infrastructure behind our training systems.
Reinforcement learning training infrastructure
Distributed training and inference systems
Experiment infrastructure and reproducibility
Large-scale data pipelines
The goal is to build the engineering foundation that allows researchers to iterate quickly while training models at massive scale.
You will architect and optimize the core training infrastructure that powers our models....
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