Member of Technical Staff Software Engineer GPU Cluster Infrastructure

Skills

About the Role

You will build and operate a self-service GPU compute platform across cloud providers. You will manage GPU lifecycle, capacity, scheduling, Kubernetes orchestration, fault tolerance, autoscaling, and observability while supporting training and low-latency inference workloads.

Requirements

• Deep Kubernetes experience with custom operators, CRDs, and multi-cluster federation
• Experience managing GPU clusters at scale
• Knowledge of NVIDIA hardware, CUDA, InfiniBand, or RoCE
• Multi-cloud compute orchestration experience
• Distributed systems knowledge of scheduling, resource allocation, and fault tolerance
• Go, Rust, or C++ systems programming skills
• Experience supporting training and high-availability inference services

Responsibilities

• Design and own a self-service GPU compute platform
• Operate GPU provisioning, lifecycle management, reliability, and capacity integration
• Build scheduling and placement logic across providers
• Support distributed training and high-availability inference workloads
• Write Kubernetes operators and CRDs for multi-cluster orchestration
• Build fault tolerance, autoscaling, and observability
• Set platform architecture and roadmap with infrastructure partners

Benefits

• Equity
• Health insurance
• Dental insurance
• Vision insurance
• Retirement benefits
• Fitness benefits
• Commuter accounts
• Dependent care accounts
• Region-tailored benefits for international full-time employees