Design a Real-Time Sensor Intelligence System
Company: OpenAI
Role: Machine Learning Engineer
Category: ML System Design
Difficulty: medium
Interview Round: Onsite
Design an end-to-end real-time sensor intelligence system for a product team.
Start from ambiguous product requirements and cover the full lifecycle:
- Identify the target use cases and success metrics.
- Choose appropriate sensors and justify the trade-offs.
- Define the data collection, labeling, storage, and training pipeline.
- Select algorithms and design the machine learning model.
- Explain how the system performs real-time inference.
- Address latency, reliability, privacy, efficiency, battery/power consumption, and hardware constraints.
- Describe how you would evaluate the model and monitor it after launch.
Assume the product must run continuously in a resource-constrained environment and produce low-latency predictions from live sensor streams.
Overview: This question evaluates proficiency in end-to-end machine learning system design for real-time sensor-driven products, covering sensor choice trade-offs, data collection and labeling pipelines, model selection and real-time inference, and operational constraints such as latency, reliability, privacy, efficiency, and power.
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