Design a large-scale Image Processing Platform

Last updated: August 17, 2025

Quick Overview

Design a real-time image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

Goldman Sachs
System Design
Software Engineer
Goldman Sachs
August 17, 2025
Software Engineer
Technical Screen
System Design
Medium

49

15

1,675 solved


Design a real-time image processing system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.

ML system design at Goldman Sachs goes beyond model selection. This Technical Screen 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
Feedback loops and model retraining
ML objective formulation and metric selection
A/B testing and experimentation
Model serving and latency optimization
How to Approach This
  1. Start by clarifying functional and non-functional requirements with the interviewer.
  2. Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
  3. Draw a high-level architecture first, then deep dive into 1-2 critical components.
  4. Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
  5. 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 ensure fairness and reduce bias in the model?
  • What would you do if model performance degrades over time?
  • What is your model retraining strategy?
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Sample Answer
Requirements

Functional Requirements

  1. Real-time Image Processing: The system should process incoming images and return results within 200 ms.
  2. Image Classification and Object Detection: Support for...
Capacity Estimation

Assuming Goldman Sachs processes around 100 million images per day:

  • Requests per second (RPS): 100 million images / 86,400 seconds = approximately 1,157 RPS.
  • Peak Load: During peak hours, ...

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