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Reddit·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
Apr 2026

Summary

Reddit ML engineer interview with a systems coding problem that felt more backend than ML. The task was to implement a simplified memcached protocol from scratch, which wasn't what I expected going in.

Questions Asked (1)

Q1

Implement a simplified memcached-style key-value server over TCP that supports get and set commands using a line-based ASCII protocol.

System DesignAPI & IntegrationsAlgorithms & Data Structures
Author's notes

Spent the first few minutes just parsing the protocol spec in my head, which was probably visible.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design a simple line-based protocol and a thread-safe in-memory store. Implement a TCP server that parses commands, handles concurrent clients, and supports basic get/set operations with optional expiration. Discuss trade-offs and potential extensions like persistence or eviction policies.

Pro tip: Mention that you would use a thread pool or async I/O to handle many concurrent connections efficiently, and that you'd consider using a read-write lock for the store to allow concurrent reads. Also, note that for ML serving, such a cache could store precomputed embeddings or feature vectors to reduce latency.

1. Clarify Requirements and Scope

Ask about expected throughput, latency, data size, persistence needs, and whether expiration is required. Confirm that only get and set are needed, and whether the protocol should be ASCII line-based.

2. Design the Protocol and Data Model

Define simple commands like 'set key value [exptime]' and 'get key', with responses like 'VALUE key value' or 'END'. Choose an in-memory hash map for storage, with optional expiration timestamps.

3. Implement the TCP Server

Use a socket server that accepts connections and spawns a thread or uses an event loop per connection. Parse incoming lines, execute commands, and send responses. Ensure thread safety with locks or concurrent data structures.

4. Handle Concurrency and Edge Cases

Address simultaneous reads/writes, partial reads, and malformed commands. Consider using a read-write lock to allow concurrent gets. Implement expiration lazily or with a background thread.

5. Discuss Trade-offs and Extensions

Talk about limitations (e.g., no persistence, no eviction) and how you might add features like LRU eviction, replication, or binary protocol. Relate to ML use cases like caching model predictions.

Key Points to Mention

  • Line-based ASCII protocol design with clear command syntax and responses
  • Thread-safe in-memory store using hash map and locks (e.g., read-write lock)
  • Concurrency model: thread-per-connection vs. event-driven (e.g., asyncio, epoll)
  • Expiration handling: lazy deletion or background sweeper
  • Error handling for malformed commands and network issues
  • Potential ML applications: caching embeddings, features, or model outputs

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.