Interview questions
LinkedIn AI engineer interview questions (2026)
4 real interview questions reported by engineers who interviewed at LinkedIn, spanning AI Engineering, Data Engineering, ML Engineering. Every question is scored against a golden answer on the things LinkedIn actually grades — architecture, token efficiency, security and correctness — not just whether your code runs.
LinkedIn ML Engineering questions
- Housing Price Outlier Detection and Visualization System
Write a function to identify and visualize outliers in a dataset of housing prices.
- Average Product Rating Calculation and Top Five Identification
Implement a top-level `solve(payload)` that ranks products by their average rating. ## The solve contract `payload` is a dict: `{"reviews": [{"product_id": str, "rating": number}
LinkedIn Data Engineering questions
- CDC Log-Based Versus Trigger-Based: Implementation Trade-offs
Explain CDC (change data capture) and contrast log-based CDC with trigger-based CDC. When would you pick each?
LinkedIn AI Engineering questions
- Location-based job recommendation system for repeat user searches
Display job postings to users in the same city based on their previous searches.
Prepare for your LinkedIn interview
Velocode turns reported LinkedIn interview questions into scored practice. Free accounts get the full community problem set and one LinkedIn-tagged question per domain; Pro unlocks every company-verified question, the interview simulator, and your domain readiness radar.