← NVIDIA Interview Insights

NVIDIA·Software Engineer·Onsite - System Design / Architecture·Senior

SeniorPrefer not to say
Jun 2026

Summary

System design round at NVIDIA for a software engineering role. The whole session was basically one big question about URL shortening, but it sprawled into a lot of sub-areas fast and I felt like I was playing catch-up by the midpoint.

Questions Asked (1)

Q1

Design a URL-shortening service like TinyURL or bit.ly. Walk through your functional requirements, how you'd generate short keys, your storage choices, caching strategy, and how you'd handle abuse.

System DesignTechnical Trade-offsData Modeling
Author's notes

I started with requirements which felt fine, listed the obvious stuff like shorten, redirect, custom aliases, expiration.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying functional and non-functional requirements, then walk through the design in a structured manner covering key generation, storage, caching, and abuse prevention. Emphasize trade-offs and scalability, and relate to NVIDIA's high-performance computing context where relevant.

Pro tip: Demonstrate awareness of real-world constraints like read-heavy workloads and the need for low-latency redirects; mention using a distributed counter or pre-generated keys to avoid collisions without coordination overhead.

1. Clarify Requirements

Ask questions to define functional requirements (e.g., shorten URL, redirect, custom aliases, expiration) and non-functional requirements (e.g., scalability, latency, availability, durability).

2. Design Key Generation

Discuss approaches for generating short keys (e.g., base62 encoding of a distributed counter, hash-based with collision resolution, or pre-generated key service) and justify your choice based on trade-offs.

3. Choose Storage and Data Model

Select a storage solution (e.g., relational DB, NoSQL like Cassandra, or key-value store like Redis) and define the data model (mapping short key to long URL, metadata). Consider sharding and replication for scale.

4. Implement Caching Strategy

Describe a caching layer (e.g., Redis or Memcached) to handle read-heavy traffic, with appropriate eviction policies and cache invalidation strategies. Discuss CDN for edge caching if needed.

5. Address Abuse and Security

Outline measures to prevent abuse (e.g., rate limiting, CAPTCHA, blacklisting malicious URLs, monitoring for spam) and ensure security (e.g., HTTPS, input validation).

Key Points to Mention

  • Read-heavy workload: optimize for fast redirects with caching and efficient storage.
  • Key generation trade-offs: centralized vs. distributed counters, collision handling, and key length.
  • Storage scalability: sharding, replication, and eventual consistency vs. strong consistency.
  • Caching strategies: TTL, LRU eviction, and cache hit ratio optimization.
  • Abuse prevention: rate limiting per user/IP, URL scanning, and reporting mechanisms.
  • Monitoring and analytics: tracking click metrics and system health for operational insights.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.