Make intelligence open and accessible to all. Backed by Battery, Lightspeed and Sequoia.
About the role
Build systems that transform powerful pre-trained models into aligned and general agents. Drive research and engineering initiatives that push the frontier of post-training, from data curation to large-scale optimization.
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.
Build systems that transform powerful pre-trained models into aligned and general agents.
Drive research and engineering initiatives that push the frontier of post-training, from data curation to large-scale optimization.
Develop data generation pipelines, reward models, reinforcement learning algorithms, and inference-time scaling techniques.
Collaborate across pre-training and post-training teams to deliver step-function gains in model capability.
Contribute to shaping our understanding of how large models learn to reason, follow instructions, and improve through reinforcement learning.
Deep understanding of machine learning fundamentals and practical experience with large-scale LLM training.
Strong engineering skills, comfortable diving into complex ML codebases and distributed systems.
Experience improving model behavior through data, reward modeling, or RL techniques.
Evidence of owning ambitious research or...
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