Design an ETA prediction system like Uber
PremiumML systemEasy
- ETA prediction
- Regression
- Residual model
Quick answer
This ML system interview question asks you to design an ETA prediction system like Uber. Aim for a design that turns data into useful predictions in production, then explain the data, training, serving and monitoring. Interviewers want to see how you frame the problem, measure success and keep the model healthy after launch.
The problem
Design an ETA prediction system like Uber's: predict how long a ride will take from pickup to drop-off, shown to the rider before they book. The hard parts are live traffic that changes by the minute, a strict latency budget at very high request volume, and errors that hurt more when the car is late than when it is early.
What must an ETA prediction system like Uber do?
- Trip ETA: Return a predicted trip duration for any pickup, drop-off and request time.
- Live traffic: Reflect traffic from the last 5 minutes.
How well must it do it?
- Latency: The model adds no more than 20 ms p99 on top of the 30 ms routing call.
- Accuracy: Mean absolute percentage error under 12% on completed trips, and under 20% in every city.
What scale should you design for?
Use these numbers in your estimates.
The scale numbers unlock with this questionUnlock
Key concepts
- ETA prediction
- Regression
- Residual model
- Real time features
- Quantile loss
- MAE
How you’ll practise
- Problem framing
- Data and labels
- Features and model
- Training and evaluation
- Serving and monitoring
- 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 ML system design round.
- Frames the product goal as a clear ML problem
- Defines offline and online success metrics
- Explains where the data and labels come from
- Separates training from serving and keeps features consistent
- Plans for drift, retraining and rollbacks
- Weighs model quality against latency and cost
Questions people ask about this interview question
- Which design type is this question?
- It is an ML system question. You design an ETA prediction system like Uber and explain your choices the way you would in an interview.
- Is this question asked at entry level?
- It is marked Easy, so it suits engineers who are new to ML system interviews. It is also a good warm-up before harder questions.
- What should I cover first?
- Start with the product goal, how success is measured and what data is available. 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