Design a large-scale Task Scheduling Platform
Last updated: July 10, 2025
Quick Overview
Design a fault-tolerant task scheduling system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
Jump Trading
July 10, 202522
14
1,412 solved
Design a fault-tolerant task scheduling system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
ML system design at Jump Trading goes beyond model selection. This Onsite question evaluates your ability to design end-to-end ML pipelines, from data collection to model serving, while considering production constraints like latency and reliability.
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
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 debug a model that works well offline but poorly online?
- What is your model retraining strategy?
- How would you handle the cold start problem?
- How would you run A/B tests on different model versions?
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Requirements
Functional Requirements
- Task Scheduling: The system should allow users to submit, update, and delete tasks. Tasks can be one-time or recurring.
- Task Prioritization: Users should be a...
Capacity Estimation
Assuming Jump Trading schedules approximately 10 million tasks per day:
- Peak Load: Let's estimate peak requests at 1000 tasks per second (considering burst traffic).
- Data Storage: If each ...
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