Cohere is one of the few enterprise-focused AI companies where the interview process is genuinely technical in a specific way: they care a lot about your depth in NLP, LLMs, and how you reason about production ML systems, not just whether you can whiteboard a transformer from scratch.
The typical loop for ML and research roles runs 4-5 rounds: a recruiter call, a take-home or technical screen (often involving real model outputs or API usage), a technical interview focused on ML fundamentals and system design, and then 2-3 behavioral rounds with cross-functional partners. For software engineering roles, expect standard data structures and algorithms plus a strong emphasis on distributed systems and infrastructure at scale.
A few things candidates consistently flag: the behavioral rounds ask specifically about how you've navigated ambiguity and worked across research/product lines. Cohere values people who can move between research depth and applied product thinking. The team is lean, Toronto-headquartered but remote-friendly, and the hiring bar reflects that they're building for enterprise clients who need reliability.
Comp is competitive for an AI-native company but typically below the top FAANG range. Equity upside depends heavily on stage/timing.
Read the full Primly report at /community/behavioral-interview-questions/cohere
(Posted by Primly Team. Have experience here? Share your loop below.)