reflectionai · San Francisco, CA
OUR MISSION 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. ABOUT THE ROLE Research Program Managers at Reflection are high-leverage leaders and operators who embed directly with research and infrastructure teams to accelerate the pace of frontier model development. They are not project trackers. They are force multipliers who bring clarity to ambiguity, drive decisions when the path forward is unclear, and ensure that the work happening across multiple teams connects into a coherent whole. This role focuses on scaling our research infrastructure to continue to support massive, frontier-scale training runs across pre-training, mid-training, and post-training. As a central mandate, you will help drive the scaling and continued evolution of our training stack. You will help gather and unify requirements, scope, and drive this scale-up rewrite of the trainer with the Research and GPU Infra engineers who build and operate our training frameworks. This role involves weaving requirements across all stages of our training pipeline: pre-training, mid-training workloads that pair the trainer with a high-throughput inference engine for RL, post-training, etc. We are looking for someone who has gone deep with GPU infrastructure teams to build training frameworks and has accumulated the scar tissue to prove it – you know firsthand which abstractions hold at 10K+ GPU scale and which ones don’t, and you can bring that judgment to a multi-quarter program of a training stack rewrite. You bring a first-responder mentality. When things go sideways, you don't wait to be asked. You jump in, assess the situation, cut through noise, align the people who need to be aligned, and drive resolution. WHAT YOU'LL DO - Own cross-functional programs spanning training infrastruc…
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