Senior Quantum Hardware Integration & Yield Engineer

Alice & Bob

Paris

Hybride

EUR 90 000 - 120 000

Plein temps

14 jours+
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Avantages offerts par ce poste

BSPCE plan
Direct IP compensation bonuses
Flexible remote policy
Parental plan with crèche support
Urban Sports Club membership
Mental health support
25-day vacation + RTT
Transportation cost coverage
Health coverage with Alan
Meal vouchers (Swile)
French language courses

Résumé du poste

Alice & Bob is seeking a Senior Integration & Yield Engineer to join the Foundries & Process Integration team in the Quantum Hardware & Infrastructure department. You will own yield monitoring across fabrication flows and lead data analysis to drive process improvements as we scale from tens to hundreds of qubits.

The role interfaces between qubit design and chip manufacturing, focusing on design-to-fab alignment, LUT management for Josephson junction fabrication, and developing Python tools to

Qualifications

  • Master's degree or Ph.D. in Physics, Materials Science, or a related field.
  • 3+ years of hands-on experience in semiconductor or superconducting circuit nanofabrication or process integration.
  • Proven expertise in yield engineering, SPC, DOE, and statistical analysis tools.
  • Proficiency in Python scripting to adapt and extend tools connecting design and fabrication workflows.
  • Strong problem-solving mindset and command of root cause analysis methodologies (5 Whys, FMEA, Ishikawa)
  • Excellent communication skills and the ability to work effectively in a cross-disciplinary environment
  • Experience in the fabrication or characterization of superconducting circuits, or in cryogenic testing is a plus

Responsabilités

  • Own yield monitoring across fabrication flows: define metrics, build automated dashboards (wafer reports), and provide real-time visibility of fab performance and yield
  • Lead root cause analysis of systematic and random yield detractors, in collaboration with the chip manufacturing teams
  • Perform advanced statistical analysis (using Python/JMP) to ensure process stability and control variability
  • Develop strategies to reduce inductance/frequency non-uniformity within and across wafers, improving the consistency of qubit performance (frequency targeting, coherence times)
  • Define and maintain robust integration flows of POR (process of reference), ensuring design-to-fab alignment
  • Establish Design for Manufacturability (DFM) guidelines
  • Document and maintain reference fabrication flows, yield dashboards, and process KPIs to support process reviews
  • Own the look-up tables (LUT) linking design parameters to Josephson junction fabrication, and maintain their accuracy as fabrication processes evolve
  • Test and implement Design Rule Manual (DRM) extensions in collaboration with the design and fabrication teams, and establish Design for Manufacturability (DFM) guidelines
  • Translate device designs into fabrication-ready wafer layouts (wafer layout generation), and develop Python-based tools to automate the design-to-wafer pipeline and reduce manual handoff errors
  • Coordinate the investigation of device failures at room and cryogenic temperatures using electrical test data, inline metrology, and advanced microscopy (SEM, AFM)
  • Lead corrective and preventive actions using structured problem-solving methodologies (5 Whys, Ishikawa)

Connaissances

Python scripting
Problem-solving
Cross-disciplinary collaboration
Communication skills

Formation

Master's degree or Ph.D. in Physics/Materials Science

Outils

Python scripting
JMP
SPC/DOE tools

Description du poste

Alice & Bob is seeking a Senior Integration & Yield Engineer to join the Foundries & Process Integration team in the Quantum Hardware & Infrastructure department. You will own yield monitoring across fabrication flows and lead data analysis to drive process improvements as we scale from tens to hundreds of qubits.

The role interfaces between qubit design and chip manufacturing, focusing on design-to-fab alignment, LUT management for Josephson junction fabrication, and developing Python tools to

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