Quantum Data Performance Engineer - Systems Integration

Requirements

• Master's Degree in Physics, Engineering, or related field.
• Experience with large-scale data analysis, statistical modeling, and visualization tools (e.g., Python, R, MATLAB, PowerBI).
• Experience building and maintaining automated data pipelines, databases, or cloud-based monitoring solutions.

Nice to Haves

• Doctorate in Physics, Engineering, or related field.
• Leveraging artificial intelligence tools and techniques to enhance data tracking, analysis, and visualization.
• Strong communication skills and a track record of translating technical data into actionable recommendations for multi-disciplinary teams.
• Demonstrated ability to independently identify and address performance risks in complex engineering systems.
• Experience with superconductor/semiconductor physics, RF measurement techniques, and/or cryogenic systems.
• Ability to be flexible and adapt to new situations in a rapidly changing research environment.
• Experience in design and analysis of experiments.
• Experience with statistical process control methodologies.

What You'll Be Doing

• Collaborating across technical pillars to understand the requirements and operational characteristics of different subsystems within the quantum computer
• Designing, implementing, and refining data pipelines for historical monitoring of key subsystem performance metrics
• Conducting advanced statistical analysis and data mining to identify performance trends, top risks, and areas for improvement across subsystems
• Documenting and communicating the results of performance tracking and analysis to stakeholders, providing actionable insights to inform system strategy and risk mitigation
• Partnering with software engineering teams to develop, maintain, and enhance code infrastructure supporting data analysis and reporting
• Proactively identifying new metrics and risk indicators to be monitored, and collaborating to stand up new data pipelines and dashboards for visibility into subsystem health and performance
• Supporting cross-functional teams in root-cause analysis and troubleshooting by providing deep dives into subsystem data and performance history

Perks and Benefits

• Ability to leverage AI tools to drive innovation and efficiency
• Ability to work in an “AI-first” environment using modern AI tools to accelerate discovery through hardware development