Group/DivisionKLA has always had a close relationship with physics and data. Our optical and electron beam inspection and measurement tools use cutting edge physics models, both for hardware design and as part of their algorithms. AI, including several traditional machine learning techniques and deep learning are routinely used to process this data to meet application requirements. The AI & Modeling Center of Excellence was setup with the mission of advancing KLA's traditional strengths in physics and data and providing implementation solutions for multiple KLA Inspection and Metrology products targeted at the semiconductor manufacturing industry. The AI & Modeling Center of Excellence is part of the company's Central Engineering organization providing product development expertise in a critical area for a wide variety KLA products. As a part of this group, you will be part of a world class team of physicists, HPC system designers, machine learning and application engineers who build cutting edge solutions for modeling complex imaging techniques and semiconductor processes. You will also work with a data scientists and AI infrastructure engineers whose mission is to build and scale machine learning based solutions for our semiconductor customers. We are looking for engineers in a few different fields. If you are passionate about Physics Modeling, High Performance Computing - HPC (including GPU), Machine Learning, Deep Learning, Data Sciences, or cutting-edge Cloud technologies - this is the place for you!
Job Description/Preferred QualificationsAs an AI Infrastructure Engineer, you will research, evaluate, and develop next-generation hardware and software technologies that enable large-scale AI and machine learning workloads across KLA. You will help design and build the infrastructure that powers model training, inference, networking, storage, data protection, and emerging agentic AI systems. This role sits at the intersection of systems engineering, AI platform development, MLOps, and DevOps, ensuring that AI teams have reliable, scalable, high-performance infrastructure to develop, train, deploy, and operate AI solutions. You will also define and develop reference architectures and platform standards that can be embraced across KLA products and engineering organizations, enabling secure, cost-effective, and repeatable AI infrastructure deployments.
Responsibilities- Design & Build AI Infrastructure: Architect, deploy, and operate scalable, secure, and cost-effective AI platforms, distributed training environments, and model serving systems.
- Research & Innovation: Evaluate emerging technologies in AI infrastructure, compute, storage, networking, orchestration, and security, and develop reference designs for enterprise adoption.
- Hardware & Software Orchestration: Bring up, integrate, and lead AI compute infrastructure while diagnosing hardware, firmware, operating system, and platform issues.
- Data & Storage Management: Design and maintain high-performance storage, networking, and data pipelines supporting large-scale AI workloads.
- Performance & Reliability: Develop observability and monitoring solutions, optimize AI workload performance, and ensure infrastructure meets reliability and availability targets.
- Security & Compliance: Implement security-by-design principles including encryption, identity and access management, secrets management, and AI data security. Contribute to the architecture and implementation capabilities for protecting AI workloads, intellectual property, and sensitive data at KLA.
- Collaboration: Partner with AI researchers, data scientists, software engineers, IT, and security teams to align platform capabilities with business and product needs.
Tools you will use in the role:- Technical Skills: Linux administration, Kubernetes/Docker, Slurm, Ray, TensorFlow, PyTorch, GPU/TPU optimization, containerization, orchestration, and programming skills.
- Infrastructure Knowledge: High speed networking, storage systems, virtualization, and server management.
- AI/ML Integration: Understanding of model training, fine-tuning, RAG pipelines, and agentic AI systems
- Automation & Scripting: Bash, Python, CI/CD pipelines, infrastructure as code (IaC).
- Security: TPM-based encryption, Kubernetes security (RBAC, OPA/Gatekeeper), container security.
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
Minimum QualificationsDoctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years
Base Pay Range: $136,300.00 - $231,700.00 Annually
Primary Location: USA-CA-Milpitas-KLA
KLA's total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave.
Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level, and location. The range displayed reflects the pay for this position in the primary location identified in this posting. Actual pay depends on several factors, including state minimum pay wage rates, location, job-related skills, experience, and relevant education level or training. We are committed to complying with all applicable federal and state minimum wage requirements where applicable. If applicable, your recruiter can share more about the specific pay range for your preferred location during the hiring process.
