Design a cloud-based data annotation platform
PremiumBackend systemHard
- Task allocation
- Workflow orchestration
- State machine
Quick answer
This backend system interview question asks you to design a cloud-based data annotation platform. Aim for a design that meets its requirements at the stated scale, then explain its main components, data flow and trade-offs. Interviewers want to see how you scope the problem, size it and defend each choice.
The problem
Design a cloud-based data annotation platform used to prepare massive datasets for AI training (e.g., autonomous driving, generative AI). ML engineering teams upload datasets containing millions of raw media items (images, videos, text). The platform must efficiently distribute these items as annotation tasks to a global workforce, track their progress, evaluate labeling consistency across multiple workers, and produce a final, highly accurate versioned dataset for model training.
What must a cloud-based data annotation platform do?
- Dataset Ingestion: Accept new datasets consisting of millions of media item URIs.
- Task Allocation: When a worker requests work, assign them an available media item they have not seen before.
What scale should you design for?
Use these numbers in your estimates.
The scale numbers unlock with this questionUnlock
Key concepts
- Task allocation
- Workflow orchestration
- State machine
- Consensus algorithms
- Blob storage
- Event driven
How you’ll practise
- Requirements
- Estimate
- API and data
- High-level design
- Deep dives
- Wrap-up
Lala, personalized to you, gives a hint when you ask and reviews your design when you are ready.
What do interviewers look for?
In any backend system design round.
- Clarifies the requirements before drawing anything
- Uses a few numbers that actually change the design
- Draws a clear path from the client to storage
- Picks storage and caching with reasons, not by habit
- Explains what breaks first under load and how to fix it
- States trade-offs openly instead of claiming a perfect design
Questions people ask about this interview question
- Which design type is this question?
- It is a backend system question. You design a cloud-based data annotation platform and explain your choices the way you would in an interview.
- Is this question asked at entry level?
- It is marked Hard. It suits engineers preparing for senior interviews, where you are expected to drive the discussion and go deep on trade-offs.
- What should I cover first?
- Start with the requirements: what the system must do, how well it must do it and which numbers change the design. Agree on scope with the interviewer before you design anything.
- Can I practise it for free?
- It is a premium question. Sign up and unlock it once for 10 credits; it then stays unlocked. When you finish, Lala, your personalized AI mentor, can review your design for 30 credits.
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Updated · Written by the SevyDevy team