Cartesia interview prep
50 Algorithm & Systems Problems
This set is built around Cartesia's real-time voice pipeline — streaming audio in and out over a socket, low-latency speech synthesis and transcription, and the session/connection management that holds a live call together — plus common infra patterns any team serving models under tight latency budgets needs. Problems are ordered by relevance, not just difficulty: the first 17 model scenarios straight out of streaming voice systems (ring buffers, jitter buffers, barge-in, backpressure); the next 17 are adjacent infra patterns (routing, caching, scheduling); the rest are classic medium/hard algorithm categories given a light Cartesia-style framing.
What's on each problem page
- The scenario, framed around Cartesia's real-time voice/infra domain, with its grounding badge.
- The actual stub function signature and docstring from the corresponding
.pyfile in../(the code you'd run locally to practice). - A step-by-step walkthrough of the solution approach — the reasoning, not just the final code.
- A "how to recognize this pattern in general" section, for transferring the approach to a novel problem in an interview.
Running the code yourself
Every problem has a matching pair of files one level up, in cartesia-coding/src/:
src/1_ring_buffer_audio_chunks.py # stub — implement the function, then run it
src/1_ring_buffer_audio_chunks_solution.py # reference solution — run it directly
python3 N_slug.py runs your implementation against the built-in test cases and
asserts they pass. python3 N_slug_solution.py runs the reference solution and
prints a step-by-step trace of its execution.
Start with Problem 1: Fixed-Capacity Ring Buffer for Streaming Audio Chunks, or jump to any problem from the sidebar.