Company profile
Weights & Biases
Weights & Biases provides experiment tracking, model evaluation, registry, and observability tools for ML teams. Interviews often focus on ML workflow fluency, developer experience, data-heavy UI systems, and the operational details of helping teams compare and reproduce model behaviour.
Interview process
Weights & Biases operates in the ml infrastructure space with a headcount around 500, which usually puts hiring in a middle zone: repeatable enough to have defined stages, small enough that the team you would join runs most of the loop. For ml engineer, ai engineer, ai infrastructure engineer candidates that generally means a recruiter conversation, skill rounds led by future teammates, and a closing conversation with a senior leader. The role pages below break down the questions for each function.
Questions and process by role
Weights & Biases hires across several engineering and product functions, and the loop shifts with each one. Open a role for the reported questions, the round-by-round focus, and a salary band for that function.
- ML engineer
ML engineer interview questions and process at Weights & Biases.
engineering - AI engineer
AI engineer interview questions and process at Weights & Biases.
ai - AI infrastructure engineer
AI infrastructure engineer interview questions and process at Weights & Biases.
ai - AI red team engineer
AI red team engineer interview questions and process at Weights & Biases.
ai - AI research engineer
AI research engineer interview questions and process at Weights & Biases.
research - MLOps engineer
MLOps engineer interview questions and process at Weights & Biases.
ai - Backend engineer
Backend engineer interview questions and process at Weights & Biases.
engineering - Analytics engineer
Analytics engineer interview questions and process at Weights & Biases.
data
Salary signal
Approximate senior median pay for Weights & Biases's core roles, anchored to San Francisco and modeled from BLS, ONS, and Levels.fyi reference medians. These are market bands for the role and city, not Weights & Biases offers. Open a role for the full city-by-city table.
Employee reviews
Weights & Biases holds a 4.2 Glassdoor rating. External review scores are directional signals. Treat them as context alongside the specific team, location, level, and hiring manager you are interviewing with.
Glassdoor 4.2