Photonics AI Engineer - Fabrication-Aware Design - Santa, Clara CA

Xanadu•,

3d•$160,000 - $210,000

About The Position

Xanadu is seeking a Photonics AI Engineer to own fabrication-aware design on a fast-paced path-finding team. The engineer will serve as the design team's authority on how fabrication processes affect designs, including layer stacks, translation from drawn to fabricated geometry, tolerance budgets, material behavior, and wafer-scale failure modes. Working closely with fabrication process engineering, the role turns wafer outcomes into design insight. It involves using automation and AI tooling to connect process data with design decisions. Xanadu primarily uses Python and its scientific ecosystem, GitHub, Docker, cloud compute, and agentic AI tools; proficiency in these technologies is essential. The position is a new opening. Base salary is determined by location, experience, and internal benchmarks, with a stated range of $160,000–$210,000 USD. The employee will also be eligible for equity and benefits.

Requirements

Fluency with modern AI tooling in day-to-day work, such as coding agents, LLM-driven automation, or agentic pipelines, and a track record of building personal tools.
Participation in multiple tapeouts with responsibility for fabrication-aware design decisions, DOE input, or post-silicon analysis.
Enthusiasm for quickly adopting new AI capabilities and reshaping workflows around them.
Comfort collaborating with ML/AI specialists on data-driven models for process and measurement data.
BSc in Physics, Materials Science, Electrical Engineering, or a related field.
Solid understanding of integrated photonics fabrication and its impact on optical performance.
Hands-on experience driving process-design co-optimization with fabrication teams.
Working knowledge of semiconductor and photonics metrology and failure analysis, including at least two of: SEM, TEM, AFM, ellipsometry, XRR/XRD, SIMS, Raman spectroscopy, and photoluminescence.
Experience with statistical analysis of wafer-level data and yield.
Strong Python skills applied to real data pipelines.
Excellent communication skills across design and process audiences.
Comfort operating in a fast-paced environment with multiple competing priorities.
Proficiency with Python and its scientific ecosystem, GitHub, Docker, cloud compute, and agentic AI tools.

Nice To Haves

MSc or PhD in Physics, Materials Science, Electrical Engineering, or a related field.
Experience building agentic systems or AI tooling for a technical domain.
Experience with integrated photonics fabrication using electro-optic materials such as thin-film lithium niobate.
Demonstrated track record of achieving low loss in integrated photonic components.
Experience with ML/AI or computer vision applied to microscopy, metrology, or inspection data.
Hands-on component design experience, including device simulation and layout.
Experience working with external foundry partners on process qualification and technology transfer.
Familiarity with quantum photonics or quantum computing hardware.

Responsibilities

Bridge fabrication and design by translating process constraints into design language and design requirements into process language.
Own the fabrication-aware layer of the design methodology, including layer stacks, geometry translation, bias and CD targets, corner definitions, and design rules grounded in measured process capability.
Keep process models calibrated against real wafer data, including CD and edge bias, sidewall angle, etch depth, film non-uniformity, and lithographic rounding.
Define tolerance and yield budgets and assess design robustness against process variation.
Contribute design requirements and test structures to fabrication experiments and DOEs.
Convert inline metrology, wafer-level optical test, imaging analysis, and yield data into design changes, building AI tooling for the feedback loop.
Lead failure analysis and distinguish design error from process excursion.