{"id":2852456,"url":"https://alion.io/job/xanadu-photonics-ai-engineer-component-inverse-design","title":"Photonics AI Engineer - Component Inverse Design","company":{"id":698,"name":"Xanadu","domain":"xanadu.ai","url":"https://alion.io/company/xanadu-ai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HiBob","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":210000,"currency":"USD","period":"year","gross":null,"usd_annual":210000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Docker","optional":false},{"name":"GitHub","optional":false},{"name":"LLM","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-19T12:59:06Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-11-05T03:31:00Z","board_verified":true,"closed_at":null,"days_open":16,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":16},"description":"About Xanadu: Xanadu’s mission is to build quantum computers that are useful and available to people everywhere.\nAt Xanadu, we are learners, innovators, researchers, collaborators and problem solvers. We are creating something that has never been built before. What we are doing is extremely hard, the classic moon shot. Few people in their life will be able to be a part of something like this, where if we are successful, the technologies we develop will solve some of the world’s most challenging problems, and literally change the world. And that is something to be excited about!\nYour role and responsibilities:\n We are looking for a Photonics AI Engineer to own component-level design on a fast-paced path-finding team at Xanadu. You will design the passive and active components at the heart of our photonic quantum hardware, pushing toward sub-milli-dB loss and broadband, fabrication-robust operation.\nYou will get there by employing, and building, agentic AI automation and ML/AI-driven optimization. We are looking for a designer who treats their own tooling as a first-class deliverable and moves as fast as AI capabilities do.\nYou will:\nOwn component design from physical concept to a verified building block ready for tapeout.\nApply ML/AI-driven inverse design and AI-assisted optimization to passive and active integrated optical components.\nRun large simulation campaigns across FDTD, EME, FEM, and mode solvers, with attention to convergence, numerical error, and compute cost.\nEstablish agentic AI tooling and processes that carries the design loop: launching simulation campaigns, triaging results, and extracting figures of merit.\nDesign for manufacturability from the start, so that simulated performance survives the fab.\nWork closely with layout, fabrication, and test engineers to close the loop from concept to measured wafer data.\nContribute reusable design and optimization infrastructure to the team's codebase.\nAt Xanadu, we primarily work with Python and its scientific ecosystem, commercial and open-source electromagnetic solvers, cloud-based high-throughput simulation, GitHub, Docker, and agentic AI tools. Proficiency in these technologies is essential.\nBasic qualifications and experience:\n\nFluency 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.\nParticipated in multiple tapeouts covering design, layout, and post-silicon analysis, with components that were fabricated and measured.\nHands-on experience applying ML/AI to a technical problem, in any domain.\nEnthusiasm for adopting new AI capabilities quickly and reshaping your own workflow around them.\nBSc in Engineering, Physics, or a related field.\nStrong knowledge of integrated photonic component design, including the sources of loss in photonic devices and their relation to the fabrication process.\nExperience with electromagnetic simulation (FDTD, EME, FEM, mode solvers) and the trade-offs between solver fidelity and computational cost.\nExperience with automated design optimization rather than manual parameter sweeps.\nStrong Python skills: reusable, tested, version-controlled code.\nComfortable operating in a fast-paced environment with multiple competing priorities.\nPreferred qualifications and experience:\n\nMSc or PhD in Engineering, Physics, or a related field.\nExperience building agentic systems or AI tooling for a technical domain.\nExperience with ML/AI-driven or inverse design of physical systems.\nExperience designing active components such as electro-optic modulators or photodiodes.\nExperience with robust or yield-aware design under process variation.\nExperience executing tapeouts with external photonic foundries.\nFamiliarity with quantum photonics or quantum computing hardware.\nThis is for a new position. Your base salary will be determined based on your location, experience, and internal benchmarks. The base salary range is 160,000 - 210,000 USD. You will also be eligible for equity and benefits.\nOur values are important. They are fundamental and lay the foundation for culture at Xanadu. Learn more about our values here.\nWe are an equal opportunity employer and encourage candidates of all backgrounds to apply. We are committed to building an inclusive, safe, and equitable culture and fostering an environment where our employees feel included, valued, and heard. We are committed to meeting the needs of all individuals and support a barrier-free workplace. Should you require accommodations at any point during the recruitment process please contact Recruiting at .\nPlease be advised that we may use artificial intelligence (AI) tools to assist in the screening and assessment of applicants for this position. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. 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