Cohere
Mid
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.
Step into this interview
Free · a live voice mock calibrated to this exact role
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
Related interviews
Cohere
Mid
Forward Deployed Engineer, Agentic Platform
Cohere
Mid
Member of Technical Staff, Applied ML
Cohere
Senior
Data Engineer, Data Foundations
Netflix
Senior
Software Engineer 5 – Agent Platform, AI Platform
Twilio
Senior
Staff, Analytics Engineer, GTM Data Science & Analytics
OpenAI
Mid