Senior
Build Reddit's next-gen ML experimentation and agentic AI platform for Ads ML
Design and build large-scale offline ML experimentation platforms, production training orchestration frameworks, and an agentic AI execution platform that powers Reddit's Ads ML lifecycle from experimentation through autonomous operations. A fit for a senior infra/platform engineer with 5+ years in distributed systems and 2+ years building production ML infrastructure who wants to define foundational tooling for multi-agent, human-in-the-loop workflows.
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
- Offline ML experimentation platform design (reproducibility, promotion workflows)
- Distributed training orchestration (hyperparameter tuning, automated retraining)
- Distributed data processing systems (Spark/Flink/Ray) and workflow orchestrators (Kubeflow/Argo/Airflow)
- Experiment tracking, lineage, model registries, artifact versioning
- Agentic AI execution platforms (multi-agent orchestration, MCP/A2A, memory/context systems)
- Partnering with ML engineers/researchers to raise experimentation velocity
常见提问方向
Design an offline ML experimentation platform that guarantees reproducibility at scale
How would you build a training orchestration framework supporting distributed training and automated retraining
Compare your experience with Spark/Flink/Ray or Kubeflow/Argo/Airflow — what tradeoffs drove your choice
Design a model registry with lineage, versioning, and rollback support
How would you architect a multi-agent orchestration system with memory/context management
Tell me about a production ML infrastructure incident and how you diagnosed it
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