Make intelligence open and accessible to all. Backed by Battery, Lightspeed and Sequoia.
About the role
Conduct critical comparative analysis to advance our understanding of model capabilities Build and refine evaluation systems and processes that create tight feedback loops between data, evals, and model behavior
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.
Conduct critical comparative analysis to advance our understanding of model capabilities
Build and refine evaluation systems and processes that create tight feedback loops between data, evals, and model behavior
Develop generalizable evaluation frameworks that capture what matters for reasoning, alignment, and usefulness.
Collaborate closely with pre-training, post-training, and applied teams to translate insights into model improvements.
Push the boundaries of what’s measurable, from synthetic evals to human feedback and real-world interaction data.
Strong statistical analysis and experimental design skills to rigorously measure model improvements
Familiarity with LLM evaluation methodologies: static benchmarks, human preference evals, and/or agentic tasks.
High agency and thrive in a fast-paced startup environment; bias for impact over process.
Excited to work in a new frontier lab, defining how we measure and...
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