Snap·Machine Learning Engineer·Technical Phone Screen
- How would you design or implement memory in an AI agent?
“I went straight to the short-term vs long-term split and talked about vector stores for retrieval.”
Large Enterprises
Most of these Snap write-ups come from Software Engineers (117), then Machine Learning Engineers (65) and Data Scientists (18). The most reported rounds are the technical phone screen (149), the system design round (45), the behavioral / leadership round (11) and the product sense round (8).
216 interview notes · updated Jul 2026
“I went straight to the short-term vs long-term split and talked about vector stores for retrieval.”
“This sounds like a warm-up but it sprawls fast.”
“I knew Manhattan distance problems lean on medians pretty quickly, so I jumped to projecting rows and columns separately.”
“This was basically a full system design compressed into one question.”
“I started with static analysis, file type checks, hashing against known malware databases, then moved into dynamic analysis in a sandbox.”
“My first instinct was to just sort the timestamps and do binary search on both ends, which works fine.”
“I started with the storage schema and probably should've asked more clarifying questions first.”
“Started with BFS which felt natural to me, got through it fine, but then they asked me to redo it with Union-Find.”
“My first instinct was Taylor series and I went with that, which is fine for small x but I didn't think about range reduction until they pushed back.”
“I started with BFS because it felt safer.”