[Remote] Photonics AI Engineer - Component Inverse Design

Note: The job is a remote job and is open to candidates in USA. Xanadu is hiring a Photonics AI Engineer to design passive and active components for photonic quantum hardware. The role uses AI-driven inverse design, optimization, and simulation to deliver fabrication-robust components, while collaborating with layout, fabrication, and test engineers and contributing reusable design tooling.

Responsibilities

• Own component design from physical concept to a verified building block ready for tapeout
• Apply ML/AI-driven inverse design and AI-assisted optimization to passive and active integrated optical components
• Run large simulation campaigns across FDTD, EME, FEM, and mode solvers, with attention to convergence, numerical error, and compute cost
• Establish agentic AI tooling and processes that carries the design loop: launching simulation campaigns, triaging results, and extracting figures of merit
• Design for manufacturability from the start, so that simulated performance survives the fab
• Work closely with layout, fabrication, and test engineers to close the loop from concept to measured wafer data
• Contribute reusable design and optimization infrastructure to the team's codebase

Skills

• Fluency with modern AI tooling in your day-to-day work (coding agents, LLM-driven automation, or agentic pipelines), and a track record of building your own tools
• Participated in multiple tapeouts covering design, layout, and post-silicon analysis, with components that were fabricated and measured
• Hands-on experience applying ML/AI to a technical problem, in any domain
• Enthusiasm for adopting new AI capabilities quickly and reshaping your own workflow around them
• BSc in Engineering, Physics, or a related field
• Strong knowledge of integrated photonic component design, including the sources of loss in photonic devices and their relation to the fabrication process
• Experience with electromagnetic simulation (FDTD, EME, FEM, mode solvers) and the trade-offs between solver fidelity and computational cost
• Experience with automated design optimization rather than manual parameter sweeps
• Strong Python skills: reusable, tested, version-controlled code
• Comfortable operating in a fast-paced environment with multiple competing priorities
• Proficiency in these technologies is essential
• MSc or PhD in Engineering, Physics, or a related field
• Experience building agentic systems or AI tooling for a technical domain
• Experience with ML/AI-driven or inverse design of physical systems
• Experience designing active components such as electro-optic modulators or photodiodes
• Experience with robust or yield-aware design under process variation
• Experience executing tapeouts with external photonic foundries
• Familiarity with quantum photonics or quantum computing hardware

Benefits

• Eligible for equity
• Hybrid work arrangement

Company Overview

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