OpenAI
Leading AI research laboratory developing state-of-the-art foundation models like GPT-4.
5 Rounds
~21 Days
Very Hard
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Software Engineer
•
Technical
•
hard
Explain how you would profile and optimize a PyTorch data loading pipeline that is currently bottlenecking GPU utilization during model training.
#PyTorch
#GPU Profiling
#I/O Optimization
#Multiprocessing
Software Engineer
•
Technical
•
hard
How would you implement KV-cache management (e.g., PagedAttention) for batched LLM inference to maximize throughput and minimize memory fragmentation?
#Memory Management
#LLM Inference
#Hardware Architecture
Software Engineer
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Technical
•
hard
Explain how you would optimize a PyTorch training loop to minimize GPU memory fragmentation.
#PyTorch
#GPU
#Memory Management
Software Engineer
•
Technical
•
hard
Describe the differences between Data Parallelism, Tensor Parallelism, and Pipeline Parallelism.
#Distributed Training
#Deep Learning
#System Architecture
Software Engineer
•
Technical
•
hard
Explain the concept of FlashAttention and why it is critical for scaling context windows in LLMs.
#Deep Learning
#Algorithm Optimization
#Hardware
Software Engineer
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Technical
•
hard
Explain how KV caching works during LLM inference. How would you optimize memory usage for it in a high-throughput environment?
#Transformers
#Memory Management
#Inference Optimization
Software Engineer
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Technical
•
hard
How do you handle out-of-memory (OOM) errors during distributed training of a multi-billion parameter model?
#Distributed Training
#Memory Profiling
#PyTorch
Software Engineer
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Technical
•
medium
Explain the differences between Tensor Parallelism and Pipeline Parallelism. When would you use one over the other?
#Distributed Systems
#Parallel Computing
#Model Architecture
Software Engineer
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Technical
•
hard
Describe how the Ring All-Reduce algorithm works in distributed deep learning.
#Distributed Algorithms
#Networking
#NCCL
Software Engineer
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Technical
•
medium
What are the trade-offs of using FP16 vs BF16 vs INT8 for model inference?
#Quantization
#Numerical Precision
#Hardware
Software Engineer
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Technical
•
hard
Explain how you would implement continuous batching (iteration-level scheduling) for LLM inference.
#Scheduling
#Inference
#Batching
Difficulty Radar
Based on recent AI-sourced data.
Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Think Out Loud
Always explain your thought process before writing code or drawing architecture.