Senior AI Systems & Platform Engineer (m/f/d)

Company Overview

KLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world’s leading technology providers to accelerate the delivery of tomorrow’s electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.

Group/Division

Enabling the movement toward advanced chip design, KLA's Measurement, Analytics and Control group (MACH) is looking for the best and brightest research scientists, software engineers, application development engineers and senior product technology process engineers to join our team. The MACH team's mission is to collaborate with our customers to innovate technologies and solutions that detect and control highly complex process variations—at their source—rather than compensate for them at later stages of the manufacturing process. With over 40 years of semiconductor process control experience, chipmakers around the globe rely on KLA to ensure that their fabs ramp next-generation devices to volume production quickly and cost-effectively. Our MACH team develops leading-edge solutions for patterning process analytics and control technologies, thereby providing customers with critical insight at the feature level, field level and cross-wafer analysis. Our teams also develop advanced modeling simulation, data analytics and process control modeling technologies. As a member of the MACH team, you’ll be joining the most sophisticated and successful process-control company in the semiconductor industry--working across functions to solve the most complex technical problems in the digital age.

Job Description/Preferred Qualifications

Solution Architecture & Platform Engineering

• Define end-to-end architecture for on-prem / air gapped AI platforms, including compute, storage, networking, and model serving layers.

• Design and implement portable AI infrastructure using open-source components (model serving, orchestration, vector storage, pipelines).

• Translate product requirements into scalable system architectures, including deployment topology and hardware sizing.

• Establish security, isolation, and resilience patterns for AI workloads in restricted environments.

• Own decisions on model hosting, orchestration, observability, and lifecycle management.
   

AI Systems & Application Integration

• Design and deploy agentic and multi-agent systems on top of production-grade infrastructure.

• Integrate reasoning, planning, and learning capabilities into reliable, observable, and maintainable systems.

• Collaborate with hardware, software, and data teams to ensure seamless deployment and usability in production environments.

• Drive integration of AI systems into existing products and workflows in semiconductor manufacturing.

Technology Leadership

• Continuously evaluate and adapt emerging AI and infrastructure technologies for real-world industrial use cases.

• Guide architectural decisions around AI infrastructure, model deployment, and system evolution.

• Contribute to building internal standards and reusable components for AI engineering across the division.

Minimum Qualifications

What you should bring for this role

• University degree in Computer Science, Electrical Engineering, or a related field.

• Strong experience in solution architecture and system design for production-grade software systems.

• Expertise in deploying AI/ML systems in on-premise, air gapped, or otherwise restricted environments.

• Hands-on experience with:
  - Model serving and inference systems (e.g. vLLM or similar).
  - Distributed systems, high-performance computing, or data-intensive platforms.
  - CI/CD and MLOps for offline or partially connected environments.

• Ability to define and evaluate hardware requirements