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Software Development Engineer — GPU Fleet Management & AI Infrastructure

AMD· Engineering
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San Jose, CA$172kFull-timePosted 1mo ago

About the role

Software engineer to build Fleet Manager, a secure control plane for operating large-scale AMD GPU infrastructure, including scheduling, workload orchestration, hardware health management, and developer-facing tools across GPU clusters.

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.
  • Implement 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.
  • Help evolve Fleet Manager into a portable orchestration layer capable of supporting Kubernetes, Slurm, Spur, and future execution environments.
  • Develop GPU health, diagnostics, quarantine, and controlled-remediation capabilities using ROCm and AMD hardware telemetry.
  • Build secure multi-tenant infrastructure with strong authentication, authorization, workload isolation, auditing, rate limiting, and least-privilege defaults.
  • Improve the reliability and performance of AI inference services, including routing, streaming, load shedding, health detection, and usage metering.
  • Define and maintain stable APIs, data models, compatibility contracts, and operational procedures.
  • Diagnose complex failures across distributed services, Kubernetes, networking, storage, GPU runtimes, drivers, and hardware.
  • Develop automated unit, integration, failure-injection, and production-readiness tests.
  • Work with AMD architecture, driver, platform, security, and machine-learning software teams to enable current and future GPU products.
  • Participate in new GPU, system, cluster, and software-stack bring-up.
  • Provide technical leadership through design reviews, code reviews, mentoring, and cross-functional problem solving.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent practical experience.

Skills

Required:Distributed systems
Nice to have:RustC++GoKubernetes internalsPostgreSQLAPIs (REST, gRPC, WebSocket)Security and multi-tenantObservability

Benefits

  • Benefits offered are described: AMD benefits at a glance (link provided in job)
Last updated Oct 22, 2026. Interested? Apply on the company site.
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