Senior AI Infrastructure Engineer

KLA-Belgium; Ann Arbor (MI); On-site; USD 130,000 - 190,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401(K) including company matching

ESPP

Job summary

KLA in the United States, Michigan (Ann Arbor) is seeking a Sr. Software Engineer to design, build, and operate production-grade AI infrastructure for large-scale GPU training and inference. You will own cluster architecture, multi-node orchestration, and performance engineering in production environments.

The role emphasizes Kubernetes, distributed systems, and open-source collaboration, with a strong emphasis on Python/Linux skills and capacity to deploy multi-node AI platforms.

Qualifications

• Bachelor's Degree and eight (8) years of Software Engineering experience.
• Four (4) years in software, cloud, platform, HPC, or infrastructure engineering, including two (2) years supporting distributed AI/ML workloads.
• Proven hands-on experience building GPU clusters from the ground up and operating them at production scale.
• Deep Kubernetes expertise, including operators, CRDs, Helm, networking, storage, scheduling, and cluster lifecycle management.
• Production experience with Ray and at least two of the following: NVIDIA NeMo RL, vLLM, SGLang, or NVIDIA Dynamo.
• Strong knowledge of NVIDIA GPUs, CUDA, NCCL, GPU Operator, DCGM, MIG, RDMA, and multi-node collective communication.
• Experience debugging training and inference performance across GPU, CPU, memory, network, and storage layers.
• Proficiency in Python and Linux, plus experience with containers, CI/CD, GitOps, infrastructure-as-code, and platform observability.
• Demonstrated open-source contribution, maintainership, or meaningful participation in an AI infrastructure project.

Responsibilities

• Design and deploy scalable, multi-node GPU clusters on Kubernetes.
• Build distributed training and reinforcement learning platforms using Ray and NVIDIA NeMo RL, supporting PyTorch/JAX.
• Deploy and optimize high-throughput LLM inference using vLLM, SGLang, NVIDIA Dynamo.
• Implement GPU scheduling, quotas, isolation, autoscaling, health monitoring, multi-tenant management.
• Profile and troubleshoot GPU workloads using Nsight, CUDA, DCGM, and related tools.
• Automate cluster provisioning, upgrades, workload deployment, and recoveries via IaC and GitOps.
• Contribute to open-source AI infrastructure communities and upstream best practices.

Skills

Python programming

Linux proficiency

Open-source collaboration

Problem-solving

Education

Bachelor's Degree in Software Engineering or related field

Tools

Kubernetes

Ray

NVIDIA NeMo RL

vLLM

SGLang

NVIDIA Dynamo

PyTorch

JAX

CUDA

NVIDIA Nsight

Job description

KLA in the United States, Michigan (Ann Arbor) is seeking a Sr. Software Engineer to design, build, and operate production-grade AI infrastructure for large-scale GPU training and inference. You will own cluster architecture, multi-node orchestration, and performance engineering in production environments.

The role emphasizes Kubernetes, distributed systems, and open-source collaboration, with a strong emphasis on Python/Linux skills and capacity to deploy multi-node AI platforms.