Working closely across all pillars, the engineer will synthesize system-level insights and communicate findings to inform technical strategy and prioritize improvements. 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 Master's Degree in Physics, Engineering, or related field. OR Bachelor's Degree in Physics, Engineering, or related field AND experience in industry or in a research and development environment 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. Ability to leverage AI tools to drive innovation and efficiency (e.g., performance modeling and analysis, research gathering, day to day task automation). Ability to work in an “AI-first” environment using modern AI tools to accelerate discovery through hardware development. Doctorate in Physics, Engineering, or related field OR Master's Degree in Physics, Engineering, or related field AND proven experience in industry or in a research and development environment OR Bachelor's Degree in Physics, Engineering, or related field AND demonstrated experience in industry or in a research and development environment OR equivalent experience. 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.