Quantum Calibration Engineer, Quantum Computing Services

Core Responsibilities

• Design data-efficient experimental routines, robust data analyses and troubleshooting workflows to extract key system parameters and insights.
• Develop, refine, and maintain calibration pipelines consisting of complex data flows.
• Develop robust data-fitting and optimization routines.
• Validate, document and track calibration results, ensuring reproducibility and traceability across different hardware and software generations, and across machine deployments.

Qualifications

• Strong proficiency in Python, including experience with data analysis and visualization libraries (e.g., NumPy, SciPy, Pandas, Matplotlib).
• Hands-on experience working with real experimental or measurement data, including noise handling, curve fitting, and model validation.
• Familiarity with optimization and regression techniques, both classical (e.g., least-squares, nonlinear fits) and statistical (e.g., Bayesian inference, parameter estimation).
• Comfort working in a hardware-facing environment, integrating software with lab instruments, data acquisition systems, or experimental control frameworks.
• Solid understanding of version control (Git) and structured software development practices (testing, modularity, documentation).
• Strong problem-solving ability, scientific curiosity, and a willingness to learn new physical systems quickly.
• Eager to grow from a capable engineer into a domain expert in quantum devices.
• Enjoys hands-on experimentation, iteration, and uncovering structure in data.
• Comfortable working across abstraction layers, from analyzing raw voltage traces to designing experiment-level calibration strategies.
• Collaborative and adaptable; able to operate in an interdisciplinary environment spanning science, software, and hardware teams.

Nice to Have

• Experience with machine learning or data-driven modeling (e.g., for pattern recognition, drift prediction, or parameter inference).
• Exposure to experimental physics or optics in a lab environment.
• Theory and practice of control systems.
• Familiarity with Kubernetes, Docker, or distributed analysis systems for scaling calibration and data pipelines.
• Knowledge of signal processing and time-series analysis for extracting trends or correlations in data.
• Proficiency in C or C++.

Education & Experience

• Bachelor's or Master's degree in Physics, Electrical Engineering, Computer Science, Applied Mathematics, or a related quantitative field.
• Candidates with diverse or nontraditional backgrounds who demonstrate strong programming and analytical skills are encouraged to apply.
• Experience or exposure to experimental research, data-driven system optimization, or hardware-software integration (through research, internships, or personal projects) is a strong plus.

Pay

The approximate base salary range for this position is $120,000 - $180,000. We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience. In addition to our base salary offerings, we also provide equity grants for all new hires.