Advanced Micro Devices, Inc

Principal Kubernetes GPU Infrastructure Engineer

Advanced Micro Devices, Inc • $150K — $200K *
Santa Clara, CA 95051In-Person
Information Technology
Less than 5 years of experience
2 months ago
Job Overview by Ladders

Qualifications

  • 5+ years of experience in AI infrastructure engineering and GPU-accelerated computing
  • Hands-on experience with Kubernetes and large-scale distributed training
  • Strong background in validating production-ready inference frameworks
  • Expertise in Kubernetes-native distributed training and scheduling
  • Proficient in optimizing AI workloads with benchmark performance analysis

Responsibilities

  • Design reference architectures for LLM training and inference using AMD GPUs
  • Architect Kubernetes-based training stacks for large-scale workloads
  • Define gang scheduling and optimize GPU placement for training
  • Deploy and optimize AMD GPU clusters with enterprise customers
  • Implement GPU orchestration and validation using Kubernetes
  • Benchmark LLM inference frameworks and produce performance playbooks
  • Create guides for communication and optimization of GPU workloads

Benefits

  • Comprehensive health, wellness, and retirement plans
  • Opportunities for career growth and development
  • Inclusive and collaborative company culture
  • Flexible working environment options
  • Access to cutting-edge technology and resources
Full Job Description
THE ROLE:

As a Principal AI Infrastructure Solution Engineer, you will partner with AMD's AI software teams and customers to enable large-scale LLM training and inference on AMD Instinct GPUs. You will design and validate production-ready Kubernetes architectures and translate inference frameworks such as vLLM and SGLang into deployable customer solutions. Your work will accelerate customer time-to-production and strengthen AMD's leadership in AI infrastructure.

THE PERSON:

You are a solution-oriented AI infrastructure engineer with strong expertise in GPU-accelerated computing and large-scale AI deployments. You excel at translating complex technologies into customer-ready solutions and delivering production-grade Kubernetes-based inference and training systems. You bring hands-on experience with Kubernetes-native distributed training, including scheduling, topology-aware GPU placement, and operating resilient, high-performance AI workloads at scale.

KEY REPSONSBILITIES:
  • Design and deliver reference architectures for LLM training and inference on AMD GPUs, from single-node to multi-datacenter deployments using Kubernetes and SLURM.
  • Architect and validate Kubernetes-based distributed training stacks for large-scale LLM workloads on AMD GPUs.
  • Define and implement gang scheduling and topology-aware GPU placement for multi-node training workloads.
  • Enable Kubernetes-native training controllers including Kubeflow Training Operator, MPI Operator, Volcano, and Kueue.
  • Partner with enterprise customers and cloud providers to deploy and optimize production AMD GPU clusters for distributed inference and multi-tenant workloads.
  • Implement and validate GPU orchestration using Kubernetes GPU Operator, device plugins, metrics exporters, and SLURM controllers.
  • Benchmark and optimize LLM inference frameworks (vLLM, SGLang) on AMD hardware, producing customer-ready performance playbooks.
  • Develop repeatable benchmarks for Kubernetes-based distributed training, covering scaling efficiency, step time, communication, and checkpointing.
  • Create tuning guides for RCCL/NCCL-equivalent communication, CPU/GPU affinity, interconnect utilization, and workload-specific optimizations.
  • Serve as the feedback loop between customers and AMD engineering, translating requirements into validated performance improvements.

PREFERRED EXPERIENCE:
  • Deployed and operated large-scale GPU clusters for production AI training and inference
  • Deep expertise in Kubernetes GPU orchestration (operators, device plugins, scheduling, multi-tenancy, observability)
  • Hands-on experience with distributed training on Kubernetes (Kubeflow, MPI Operator, Volcano, Kueue, Ray)
  • Strong knowledge of gang scheduling, elastic jobs, quotas, priority, and shared GPU environments
  • Tuned Kubernetes networking and storage for AI workloads (high-performance CNI, RDMA where applicable, scalable checkpointing)
  • Implemented ML observability for training (GPU/comms metrics, step-time analysis, SLO-driven ops)
  • Experience in AI/ML infrastructure, solution architecture, and production GPU deployments
  • Proven success enabling customers through complex AI platform deployments and migrations
  • Strong background working across engineering and customer-facing roles
  • Understanding of AI accelerator architectures and inference optimization techniques
  • Experience operationalizing Kubernetes-based distributed training at scale
  • Open-source contributions or AI infrastructure community engagement (plus)


LOCATION:
  • Santa Clara, Ca or open to discuss other locations.


This role is not eligible for visa sponsorship.

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Benefits offered are described: AMD benefits at a glance.

About Advanced Micro Devices, Inc

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Join the innovative forefront of technology with a career at Advanced Micro Devices, Inc. (AMD), a leader in semiconductor development. As part of our global team, you will contribute to an organization renowned for its dedication to innovation, leadership, and diversity in the tech industry.

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Join a team of over 12,000 dedicated professionals at the intersection of technology, industry expertise, and digital innovation. At AMD, you will work on groundbreaking projects that shape the future of computing and graphics. Our collaborative environment encourages networking and the sharing of ideas across teams and disciplines.

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AMD is committed to the development of its employees. We offer robust training programs, including leadership development and diversity training, to ensure our team is equipped for both current challenges and future opportunities. Our benefits package is designed to support the well-being and financial security of our employees and their families.

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Learn more about Advanced Micro Devices, Inc
Size
15,500 employees
Market Cap
$100.9 billion
Industry
Manufacturing & Automotive
Net Income
$2.4 billion
Founded
1969
5 Year Trend
+30.9%
Revenue
$9.7 billion
NASDAQ
AMD
* Ladders Estimates

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