Principal Systems Analyst

Onto Innovation•Milpitas, CA

3d•$115,200 - $172,800

About The Position

Onto Innovation is a leader in process control, combining global scale with an expanded portfolio of leading-edge technologies that include: 3D metrology spanning the chip from nanometer-scale transistors to micron-level die-interconnects; macro defect inspection of wafers and packages; metal interconnect composition; factory analytics; and lithography for advanced semiconductor packaging. Our breadth of offerings across the entire semiconductor value chain helps our customers solve their most difficult yield, device performance, quality, and reliability issues. Onto Innovation strives to optimize customers’ critical path of progress by making them smarter, faster and more efficient.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data & Analytics, or equivalent practical experience.
5–7 years of overall professional experience delivering technical solutions, automation, analytics, or software development in an enterprise environment.
Experience enabling or supporting other teams in adopting new technologies or technical capabilities.
Strong analytical and problem-solving skills, with the ability to navigate ambiguous problem spaces and large data sets
Excellent communication skills, with the ability to work effectively across technical and non‑technical stakeholders.
Demonstrated experience architecting enterprise-grade AI or advanced analytics solutions, from use-case definition through production deployment.
Hands‑on experience with Python, PowerShell, and/or other scripting languages for automation, integration, and data processing.
Experience building or supporting AI enabled solutions using enterprise AI tools and platforms (not custom LLM development).
Experience working in a Microsoft‑centric enterprise environment, including Microsoft AI, automation, and data platforms.

Nice To Haves

Experience in manufacturing, semiconductor, high‑tech, or capital equipment environments.
Familiarity with additional AI tools and platforms beyond Microsoft (e.g., Claude or similar technologies), applied in a pragmatic, enterprise context.
Experience contributing to technology evaluation, pilot programs, or platform standardization efforts.
Experience working across both cloud and on-prem systems.

Responsibilities

Architect end‑to‑end AI solutions, defining patterns for data ingestion, model usage, orchestration, validation, security, and integration into enterprise systems.
Enable teams across IT, Finance, HR, Legal, Operations, Supply Chain, Engineering, and other functions to adopt AI effectively and responsibly.
Act as a hands-on technical advisor, helping teams shape AI use cases, solution designs, and implementation approaches.
Provide guidance on when and how AI should be applied versus traditional automation or analytics.
Evangelize AI and co-lead AI cross functional AI champion network.
Develop reference examples, patterns, and lightweight guidance that help teams’ self-serve while remaining aligned to enterprise standards.
Design and implement AI enabled workflows, automation, and analytics solutions where direct development is required.
Prototype solutions, validate value, and mature successful approaches into reusable or production ready implementations.
Support integration of AI outputs into business processes and systems, including reporting, decision support, and operational workflows.
Balance speed with maintainability by applying appropriate documentation, validation, and operational considerations.
Evaluate emerging AI tools, platforms, and capabilities to determine enterprise fit and risk.
Build ROI measurement frameworks for rollout of AI capability.
Provide informed recommendations on adoption, pilots, or rejection of AI technologies in partnership with IT, Security, and Data & Analytics leadership.
Help ensure a controlled and intentional expansion of Onto’s AI toolset over time.
Partner with data owners and analytics teams to ensure AI solutions leverage trusted, governed data sources.
Apply strong analytical thinking to measure impact, validate outputs, and communicate results.
Support development of metrics and reporting to track AI adoption and value realization.
Define and enforce AI architecture patterns that align data classification, access control, and least-privilege principles with enterprise security and governance standards.
Ensure AI solutions align with enterprise security, privacy, compliance, and IP protection requirements.
Promote responsible AI practices, including transparency, appropriate human-in-the-loop validation, and awareness of tool limitations.
Help reinforce consistent, responsible AI usage practices through examples and guidance.