Forward Deployed Engineer

KLA•Ann Arbor, MI

8d•Onsite

About The Position

This role sits at the intersection of KLA's most advanced AI work and the rest of the company. Based in Ann Arbor, you are the bridge between what our AI engineering team builds and what KLA's business units need — identifying which capabilities are ready to deploy and building the infrastructure that every future AI deployment stands on. You own the internal AI platform that raises the capability floor across the organization. If you want to build foundational AI infrastructure at a company where the data is proprietary, the problems are hard, and the impact is measurable — this is the role. This role sits at the intersection of KLA's most advanced AI work and the rest of the company. Based in Ann Arbor, you are the bridge between what our AI engineering team builds and what KLA's business units need — identifying which capabilities are ready to deploy and building the infrastructure that every future AI deployment stands on. You own the internal AI platform that raises the capability floor across the organization.

Requirements

Bachelor's degree in Computer Science, Software Engineering, or related field; Master's preferred
3+ years of experience building and operating ML/AI systems in production, including ownership of production-grade infrastructure
Strong proficiency in Python and experience with ML frameworks and model fine-tuning techniques
Hands-on experience with inference optimization and model serving infrastructure, including on-prem deployment patterns
Experience building internal tools, platform infrastructure, or developer experience layers that other engineers or non-technical users depend on
Experience designing plugin architectures, marketplace systems, or extensible platform components that scale adoption
Experience building persistent memory, context management, or personalization systems for AI products
Working knowledge of CI/CD, containerization, orchestration, and Infrastructure-as-Code
Experience designing evaluation harnesses and automated testing for AI systems
Strong understanding of data governance and security — comfortable operating within tiered data handling policies
Owns outcomes, not tasks — you identify what needs to happen and drive it without being managed
Technical leadership experience: mentoring engineers, leading design reviews, setting standards
Doctorate (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

Nice To Haves

Prior experience in semiconductor, manufacturing, or scientific/industrial ML is a plus

Responsibilities

Build and enhance AI products and tools for the business, owning product quality and reliability end to end
Deploy AI capabilities into KLA's teams, serving as the bridge between R&D and production use
Own the internal AI infrastructure — the foundational layer that removes friction, compounds organizational learning, and scales without adding headcount
Architect and maintain reusable infrastructure: agent scaffolding, eval frameworks, and integration patterns
Design and build persistent context and memory systems that make AI environments personalized and progressively more useful over time
Build skill and plugin distribution systems that let one person's breakthrough become everyone's baseline
Design and operate on-prem inference infrastructure for deployments where data cannot leave the network
Fine-tune or adapt foundation models on proprietary data where it creates meaningful capability uplift
Build CI/CD pipelines for agents: testing, evaluation, versioning, and rollback
Set technical standards and mentor junior engineers; lead design reviews and define golden paths for development
Track the AI frontier at a deep technical level — not just what shipped but how it works and what it changes about what's possible