AI Infrastructure Systems Engineer

Aimlroles; Milpitas (CA); On-site; USD 136,000 - 200,000; Full time

Job summary

KLA is hiring a Systems Software Engineer - AI Infrastructure in Milpitas, CA to build and operate scalable AI platforms, training environments, and model serving systems. The role sits at the intersection of systems engineering, AI platform development, MLOps and DevOps.

You will work with AI researchers, data scientists and software engineers to design secure, high-performance infrastructure for AI across products and labs.

Qualifications

• Degree in Computer Science, Computer Engineering, or related field
• 5–8 years in systems engineering, DevOps, or ML infrastructure
• Hands-on experience building AI/GPU cluster

Responsibilities

• Design & Build AI infrastructure: architect, deploy, and operate scalable AI platforms and model serving systems.
• Research & Innovation: evaluate emerging technologies and develop reference designs for enterprise adoption.
• Hardware & Software Orchestration: bring up, integrate, and lead AI compute infrastructure while diagnosing issues.
• Data & Storage Management: design and maintain high-performance storage, networking, and data pipelines.
• Performance & Reliability: develop observability and monitoring solutions, optimize AI workloads for reliability.
• Security & Compliance: implement security-by-design principles for AI workloads and data protection.
• Collaboration: partner with AI researchers, data scientists, software engineers, IT and security teams.

Skills

Linux administration

Kubernetes & Docker

Slurm

Ray

TensorFlow

PyTorch

GPU/TPU optimization

Containerization

Orchestration

Programming skills

Education

Degree in Computer Science, Computer Engineering, or related field

Tools

Kubernetes

Docker

Slurm

Ray

TensorFlow

PyTorch

GPU/TPU optimization

Job description

KLA is hiring a Systems Software Engineer - AI Infrastructure in Milpitas, CA to build and operate scalable AI platforms, training environments, and model serving systems. The role sits at the intersection of systems engineering, AI platform development, MLOps and DevOps.

You will work with AI researchers, data scientists and software engineers to design secure, high-performance infrastructure for AI across products and labs.