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Prove your data-quality and eval rigor for training frontier LLMs at Cohere

Cohere is hiring a Member of Technical Staff for its Modeling team to design data collection tasks, evaluate dataset quality, and assess the robustness of its large language models. This role sits at the intersection of statistics, human-annotation experimental design, and hands-on LLM training, remote-friendly across Cohere's global offices.

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What this interview tests

  • Experimental design with human annotators
  • Statistical evaluation of dataset/model quality
  • LLM training on distributed infrastructure
  • Model robustness and generalizability analysis
  • Cross-functional collaboration with researchers and annotators

Common question themes

Design a data collection pipeline with human annotators and quality controls

Statistical methods for evaluating dataset reliability and bias

Diagnosing why a model fails to generalize across use cases

Hands-on experience fine-tuning LLMs on distributed training infrastructure

Communicating data-driven findings to cross-functional research/engineering teams

How candidates describe it

Real Member of Technical Staff interview stories — retold from candidates' public write-ups, with sources.

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