Data Scientist, Quantum Integrated Circuit Design Calibration

Rigetti Computing•Fremont, CA

16d

About The Position

As a Data Scientist in the quantum integrated circuit design team, you will play a critical role in our design, fabrication and test flywheel. Through comprehensive and robust analysis of large, ever-expanding datasets obtained from existing quantum processors and test devices, you will extract relevant empirical calibrations to improve the accuracy of our processor design and the performance of subsequent generations of processors. You will develop software infrastructure to streamline and automate these analyses to accelerate learning cycles. Finally, you will collaborate closely with researchers and engineers across Rigetti to monitor and improve fabrication yield, and improve the models and infrastructure used to predict processor performance from foundry metrology data.

Requirements

Undergraduate degree in Computer Science, Physics, Applied Physics, Electrical Engineering, or a related field.
6+ years of experience in data science and statistical analysis in a scientific field, with experience ranging from extracting statistically significant signals from small datasets to experience efficiently visualizing and analysing very large datasets
Programming skills in Python for scientific applications, ideally in an industry or highly collaborative environment.
Experience with SQL or similar database querying tools
Experience collaborating with experimentalists to analyze & interpret experimental data
Ability to excel in a collaborative environment.
Excellent communication skills.

Nice To Haves

Knowledge and/or direct experience with integrated circuit fabrication and lithographic techniques, and the monitoring and optimization of related fabrication processes
Experience in a technical role within an industry or startup environment

Responsibilities

Design and implement industry grade software infrastructure in python to streamline feedback from measurement to the integrated circuit design team.
Identify correlations between fabrication metrology data and processor performance through the analysis of empirical datasets, leveraging these correlations to better predict performance prior to packaging and test.
Utilize techniques and best practices in statistical analysis and machine learning to accurately calibrate various processor design parameters, leveraging the large datasets generated from measurements on our quantum processors and dedicated monitoring devices.
Collaborate closely with engineers and scientists at Rigettiâs quantum foundry to monitor and improve fabrication yield, and identify the highest yielding candidate processors for subsequent test and deployment.