Scale Engineer

Software Engineer

Software EngineerL5Hard

This interview process is designed to assess candidates for the Software Engineer (L5) role at OpenAI. It evaluates technical proficiency, problem-solving skills, system design capabilities, and cultural fit within OpenAI's innovative and collaborative environment.

Rounds·4

Timeline·~14d

Experience·5 - 10 yrs

Comp band·US$180000 - US$250000

Interview time·210 min

Evaluation

What they measure.

  • Problem-solving ability
  • Algorithmic thinking
  • Data structures knowledge
  • Code quality and efficiency
  • Debugging skills

Preparation

How to prepare.

Tips

  1. Thoroughly review fundamental data structures and algorithms.
  2. Practice coding problems on platforms like LeetCode (focus on Medium/Hard).
  3. Study system design concepts, including scalability, availability, and consistency.
  4. Prepare to discuss past projects in detail, focusing on your contributions and technical decisions.
  5. Understand OpenAI's mission, research, and products.
  6. Practice behavioral questions using the STAR method.
  7. Be ready to articulate your thought process clearly during problem-solving.

Study plan

Fig · Study plan — 04 phases

01 / 04
01

Phase 01 of 04

Data Structures and Algorithms

Weeks 1-2: Data Structures & Algorithms fundamentals. Practice 40-60 problems.

Weeks 1-2: Focus on core data structures (arrays, linked lists, trees, graphs, hash tables) and algorithms (sorting, searching, dynamic programming, graph traversal). Practice implementing these from scratch and analyze their time/space complexity. Solve at least 20-30 problems per week.

Questions

Commonly asked.

  • Given a stream of user activity logs, design a system to detect fraudulent behavior in real-time.
  • Implement a function to find the k-th largest element in an unsorted array.
  • How would you design a distributed cache system for a popular website?
  • Describe a time you had a conflict with a teammate and how you resolved it.
  • What are the trade-offs between SQL and NoSQL databases for a specific use case?
  • Write a function to reverse a linked list.
  • How would you design a system to handle millions of concurrent WebSocket connections?
  • Tell me about a challenging technical problem you faced and how you overcame it.
  • Explain the concept of eventual consistency and when it's appropriate to use.
  • Design an API for a ride-sharing service.

Locations

Regional differences.

Fig · Regions — 02 locations

01 / 02

Location

San Francisco Bay Area

Interview focus

Understanding of regional technical infrastructure and challenges.Awareness of local market trends and user behavior.Experience with region-specific compliance and data regulations.

Common questions

  • Discuss a challenging distributed system you designed or worked on.
  • How would you handle scaling a service to millions of users in a specific region?
  • What are the key considerations for data privacy and security in your region?
  • Describe your experience with local regulatory compliance related to technology.

Tips

  • Research OpenAI's presence and projects in the specific region.
  • Be prepared to discuss how your experience aligns with regional technical needs.
  • Familiarize yourself with any relevant local tech communities or initiatives.

Rounds

Round-by-round.

Expand a step for evaluation criteria, sample questions, and prep notes.

DSA

Coding questions at OpenAI.

Frequently reported on OpenAI loops

View all at OpenAI

Other guides

More at OpenAI.