Design a scalable Data Pipeline System
Last updated: June 8, 2026
Quick Overview
Design a scalable data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
xAI
System Design
Software Engineer
xAI
June 8, 2026Software Engineer
Onsite
System Design
Medium
71
8
1,698 solved
Design a scalable data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
xAI asks this during the Onsite to assess your understanding of the full ML lifecycle. They want to see how you translate a business problem into an ML objective, design the feature pipeline, and plan for model monitoring and retraining.
What the Interviewer Expects
- Define clear ML objectives with appropriate loss functions and metrics
- Design a comprehensive feature engineering pipeline
- Discuss model selection with trade-offs (complexity vs interpretability vs latency)
- Plan online and offline evaluation strategies including A/B testing
- Address serving infrastructure: batch vs real-time, latency requirements
- Consider data quality, labeling strategy, and feedback loops
Key Topics to Cover
A/B testing and experimentation
Monitoring and model degradation detection
Feedback loops and model retraining
Training pipeline and infrastructure
Model selection and architecture
ML objective formulation and metric selection
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- How would you run A/B tests on different model versions?
- How would you handle the cold start problem?
- What would you do if model performance degrades over time?
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Requirements
Functional Requirements
- Data Ingestion: The system should be able to ingest data from various sources including user interactions, logs, and third-party APIs with millions of requests per d...
Capacity Estimation
Assuming xAI anticipates handling 10 million requests per day:
- Requests per second: 10 million requests / 86,400 seconds = ~115 requests/second.
- Data Size: If each request generates an ave...
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