GPU Fleet Orchestrator for AI Infra

Advanced Micro Devices; San Jose (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Advanced Micro Devices is seeking an experienced software engineer to build Fleet Manager, a secure control plane for operating large-scale AMD GPU infrastructure.

You will design and develop distributed services spanning Kubernetes, GPU scheduling, inference infrastructure, and developer‑facing APIs and tools. The role combines systems software, cloud infrastructure, and accelerated computing.

Qualifications

• Strong systems‑software development experience in Rust, C++, Go or a comparable language.
• Experience designing and operating distributed systems, control planes, schedulers, or cloud infrastructure.
• Strong understanding of concurrency, asynchronous programming, state machines, and failure recovery.
• Experience building reliable services using REST, streaming, WebSocket, or gRPC APIs.

Responsibilities

• Design and develop Fleet Manager’s distributed control‑plane services, APIs, schedulers, inference gateway, and command‑line tools.
• Build reliable orchestration for GPU training, inference, custom jobs, and interactive development workloads.
• Develop scalable scheduling and admission‑control capabilities, including priority, fairness, topology‑aware placement, quotas, backfilling, and multi‑node workload coordination.
• Develop durable reconciliation, lifecycle management, retries, idempotency, and recovery across PostgreSQL and external execution systems.
• Integrate Fleet Manager with Kubernetes and technologies such as Kueue, JobSet, container runtimes, storage systems, and observability platforms.

Skills

Rust

C++

Go

Distributed systems

Kubernetes

PostgreSQL

REST APIs

gRPC

Security

Multi-tenant

Education

Bachelor’s or Master’s degree in Computer Science / Engineering

Tools

Kubernetes

Kueue

JobSet

PostgreSQL

Job description

Advanced Micro Devices is seeking an experienced software engineer to build Fleet Manager, a secure control plane for operating large-scale AMD GPU infrastructure.

You will design and develop distributed services spanning Kubernetes, GPU scheduling, inference infrastructure, and developer‑facing APIs and tools. The role combines systems software, cloud infrastructure, and accelerated computing.