Netflix
Mid
Build internal Python platform tooling and libraries for Netflix engineering
Netflix is hiring for its newly formed Python Platform team, responsible for the internal libraries, runtime management, and developer experience that power Python usage across Netflix's ML, data science, and animation pipeline work. The role emphasizes performance optimization for Python web services and GPU-integrated workloads, plus close collaboration with internal developer customers.
走进这场面试
免费 · 一场按这个岗位校准的真语音模拟
这场面试考什么
- Python web stack performance optimization (FastAPI, Flask)
- GPU-integrated Python workloads (CUDA-aware Python, TensorRT, torch.compile, ONNX)
- Internal developer platform / library design
- Low-latency, high-throughput distributed systems performance
- Judgment on risk-aware change management for foundational infra
常见提问方向
Walk through a real Python performance optimization you did — how did you profile and what changed?
How would you decide what functionality belongs in a shared internal Python library vs. team-owned code?
Describe your hands-on experience integrating Python with GPU workloads (CUDA, TensorRT, or similar)
Tell me about a time you chose a conservative, lower-risk technical approach over a more modern one, and why
How do you gather requirements from internal 'customers' (other engineering teams) and prioritize platform work?
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