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Amazon

Senior

Own testing/monitoring infrastructure for EC2's largest AI/ML network stacks

Interview for a Senior Software Engineer role on Annapurna Labs' ML Network Stack team, which supports frameworks like NCCL, NVSHMEM, and NIXL for EC2's distributed AI/ML systems. The role focuses on building the infrastructure that monitors, benchmarks, and reports on performance/functional regressions across massive-scale testing workloads.

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这场面试考什么

  • Networking and HPC/RDMA interconnects for distributed AI/ML systems
  • Building automated testing/benchmarking infrastructure at scale (Python, CI/CD)
  • Performance data pipelines and dashboarding (Grafana, Athena)
  • Automatic regression/anomaly detection across instance types and software stacks
  • SW/HW co-design and technical leadership/mentoring

常见提问方向

Design a system to automatically spin up large ML/HPC clusters, run benchmarks, and detect performance regressions before they reach customers

Walk through your experience with NCCL, RDMA, or high-speed networking internals in a distributed ML context

How would you build a dashboard pipeline from raw performance telemetry (e.g., via Grafana/Athena) to actionable developer alerts

Describe a SW/HW co-design tradeoff you made and how it affected system performance or reliability

Tell me about leading or mentoring a team through building test infrastructure that had to scale across many instance types and OS versions

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