Senior Platform Engineer — GPU Inference & Training

Neura Market; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Perplexity is building a self-serve compute platform that lets inference engineers run training jobs and inference services without worrying about GPU provisioning or cluster configuration. You will own the platform surface and drive reliability, observability, and performance across workloads.

You’ll manage the Kubernetes for GPU orchestration, multi-cloud GPU fleets, and capacity planning, aiming for a seamless experience that hides complexity behind a unified platform and scalable

Qualifications

• Deep Kubernetes experience—custom operators, CRDs, and multi-cluster federation.
• Managed GPU clusters at scale: NVIDIA hardware, CUDA, and the networking that makes them fast (InfiniBand or RoCE).
• Orchestrated compute across multiple clouds (CoreWeave, AWS, GCP, or similar) and understood how different each one really is.
• Strong distributed systems fundamentals: scheduling, resource allocation, and fault tolerance under load.
• You write infrastructure and systems-level code in Go, Rust or C++.
• You've supported both long-running training jobs and high-availability inference services, and you know why they pull infrastructure in opposite directions.
• You own problems end-to-end and do well when the path forward isn’t laid out for you.

Responsibilities

• Build a self-serve compute platform.
• Operate the GPU fleet.
• Solve for GPU scarcity.
• Support two very different workloads.
• Own the Kubernetes for GPU orchestration.
• Make failure boring.
• Set technical direction across teams.

Skills

Kubernetes

GPU clusters

Multi-cloud

Distributed systems

Go/Rust/C++

Production workloads

End-to-end ownership

Tools

CUDA

Prometheus

Grafana

Job description

Perplexity is building a self-serve compute platform that lets inference engineers run training jobs and inference services without worrying about GPU provisioning or cluster configuration. You will own the platform surface and drive reliability, observability, and performance across workloads.

You’ll manage the Kubernetes for GPU orchestration, multi-cloud GPU fleets, and capacity planning, aiming for a seamless experience that hides complexity behind a unified platform and scalable