Editorial practice groupings, not verified official interview questions or endorsements.
Public ElevenLabs prep guide
Prepare with five practice prompts shaped by two public candidate pages: synchronising audio playback with transcript highlighting, designing a review interface for a voice-dubbing project, fixing a practical React problem live, clearing a 90-minute assessment that mixes React tasks with medium algorithms, and streaming generated audio and text to the screen.
This guide uses public, candidate-sourced pages to create realistic constraints. It does not claim access to private interview material, a fixed interview format, or the stack of every ElevenLabs team.
Study priorities
The public accounts reward engineers who can make a media interface truthful under time: a highlight that follows playback without drifting, a review screen that keeps an editor and voice actors in sync, a fix that addresses the cause of a bug rather than its symptom. Each prompt below starts with the clarifying questions a strong candidate asks, then the behaviours a strong answer covers, then the miss that usually ends the round.
The senior account describes a timed assessment of four questions in about 90 minutes, mixing React tasks with medium algorithm problems, followed by a live session fixing a practical problem with the interviewer. Practice both shapes with a clock running, and narrate your decisions while you type.
Role lenses
These are preparation lenses derived from the public prompts and the kinds of screens an AI voice company runs, not claimed team assignments. Choose the lens closest to the role and keep the reasoning framework-neutral.
Dubbing and voice-editing screens combine timelines, playback, transcripts, review states and feedback from several people on one project.
Practice focus: Time-driven rendering, playback-synchronised highlighting, review and approval state, optimistic edits with recovery, and keyboard-driven editing.
Consoles and demos that generate audio from text, stream the result, show usage and quotas, and must stay honest while a request is in flight.
Practice focus: Streaming reads, cancellation, loading and failure states, idempotent generation requests, and accessible controls for play, pause and seek.
Representative practice prompts
For each prompt, clarify the contract, explain ownership and trade-offs, implement or diagram the smallest credible slice, and test the failure cases. Prompts modelled on a public report link to it; the fifth prompt is derived from the product domain and carries no report.
Prompt 1
Given an audio element and a transcript with start and end times per word or segment, highlight the segment being spoken as playback runs, and keep it correct through play, pause, seek and speed changes.
Practice version modelled on a reported round: Public report: ElevenLabs candidate-sourced question bank on Aced, October 2026
Choosing a time source and update loop, mapping a timestamp to a segment efficiently, rendering only what changed, and reasoning about drift and edge timings.
Common miss: Relying on the timeupdate event alone, which fires a few times per second, so the highlight lags and skips short words.
Practice high-frequency UI updates (Premium)Prompt 2
An editor manages a dubbing project in a spreadsheet today. Design the interface that replaces it: review progress across languages and lines, collect and resolve feedback, and let voice actors collaborate without overwriting each other.
Practice version modelled on a reported round: Public report: ElevenLabs candidate-sourced question bank on Aced, October 2026
Product decomposition, state ownership across roles, review and approval workflows, optimistic edits with conflict handling, and what to show when a job is still processing.
Common miss: Designing the happy path only, with no story for a failed regeneration, a stale comment or two people editing the same line.
Work through the AI-assisted review flow case (Premium)Prompt 3
You receive a small working app with a real bug: a result that lags behind the input, an effect that runs with stale values, or a request whose late response overwrites a newer one. Reproduce it, explain the cause and fix it while talking.
Practice version modelled on a reported round: Public report: ElevenLabs senior full-stack (frontend-leaning) interview account on Aced, 2026
Reading unfamiliar component code, reproducing before editing, reasoning about effects, closures and request ordering, and communicating a root cause under time.
Common miss: Patching the symptom, for example forcing a re-render or adding a delay, while the race or stale closure stays in place.
Fix the async race in fetchWithCachePrompt 4
Four questions in about ninety minutes: React tasks alongside medium algorithm problems such as reversing a linked list or finding the longest substring without repeating characters. Allocate time, ship working code and move on.
Practice version modelled on a reported round: Public report: ElevenLabs senior full-stack (frontend-leaning) interview account on Aced, 2026
Time allocation under a clock, clean React fundamentals without a framework crutch, and the ability to produce correct, tested code for mid-level algorithm problems.
Common miss: Spending half the clock polishing the first React task and leaving an algorithm problem untouched.
Practice the React autocomplete starter against a clockPrompt 5
Build the playback surface for a text-to-speech request: start playing as chunks arrive, show the text being voiced, let the user stop or regenerate, and never let a late chunk from an old request reach the new one. This prompt is derived from the product domain, not from a public report.
Streaming reads, request identity and cancellation, media element control, and truthful status while a generation is in flight.
Common miss: Appending chunks to the player without checking which request they belong to, so a regenerated line plays two voices.
Practice reading a stream to textPublic mini walkthrough
Treat this as a representative exercise, not a description of the reported one. Work from the contract toward the loop, and say each decision out loud.
The timeupdate event fires a few times per second. Read currentTime inside a requestAnimationFrame loop while playing, and stop the loop on pause.
Keep start times sorted and binary-search the active index. Cache the last index so a forward step checks one neighbour first.
Store the active index, not a flag on every segment, so a long transcript does not re-render on each frame.
Seek backwards, change the playback rate, pause mid-word, reach the end, and handle a gap between two segments.
Actionable preparation
Every day ends with code, a test, a design artifact, or a question you can use in the real process.
Media timing: requestAnimationFrame loops, currentTime, binary search over timestamps, rendering only the active segment.
Deliverable: A transcript highlighter that survives seek and rate changes.
Review workflows: entities with explicit status, comments bound to versions, conflict handling.
Deliverable: A one-page state and recovery diagram for a dubbing review screen.
Debugging live: stale closures, overlapping requests, derived state; narrate every step.
Deliverable: The async-race fix with a written root cause.
Timed drills: two React tasks and two medium algorithm problems in ninety minutes.
Deliverable: Four submissions with a time log.
Streaming playback: request identity, AbortController, media element control, status states.
Deliverable: A streaming player that ignores chunks from a cancelled request.
Product thinking: decompose one creator workflow into UI, API and jobs; name the failure states.
Deliverable: A written decomposition with open questions for the interviewer.
Mock loop: one timed assessment, one live fix, one design walkthrough, each narrated.
Deliverable: A list of the questions you will ask the recruiter about format, tools and stack.
Preparation FAQ
No. They are FrontendAtlas practice versions modelled on prompts listed in a candidate-sourced bank and on one senior interview account. The wording, the data and the test cases are ours.
One public account describes about ninety minutes for four questions mixing React tasks with medium algorithm problems. One account cannot establish the current format; confirm it with the recruiter.
The public prompts are about interface behaviour around audio: synchronising a highlight with playback and reviewing dubbing work. Comfort with media elements, timing and streaming matters more than signal processing.
The public account mentions React tasks and the senior role was titled full-stack, frontend-leaning. Prepare the same contracts in your own framework first, then once in React.
Free public practice
These public pages cover the streaming, timing, debugging and communication skills used by the practice prompts. They are supporting drills, not claimed ElevenLabs questions.
Public interview reports and official context
These links support the public context used by the guide. Their notes state what each source can and cannot establish about preparation.
A question bank marked as updated by ElevenLabs candidates. It establishes that the audio-transcript synchronisation exercise and the voice-dubbing review prompt were listed; it cannot establish wording, frequency or which role each belongs to.
One self-reported senior account: recruiter screen, a 90-minute four-question assessment mixing React tasks and medium algorithms, then a live practical fix. It cannot establish the current format or the loops of other teams.
Official roles and teams for product context only, not evidence of interview content or format.
Full company practice
This public guide is complete enough to plan a focused week. Premium unlocks the AI-assisted review flow case, the timer-manager drill and the broader company-tagged editorial set.