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Microsoft Quantum has assembled a talented and diverse international team to create the world’s first scalable quantum computing system. The research effort includes a diverse staff of theoretical and experimental physicists, hardware designers and software engineers around the world collaborating in a very fast-paced environment, where good communication and good documentation are key to the success of the program. This role sits on the software team building the control, measurement, and bring-up stack for Microsoft’s topological qubit chips and the broader quantum machine we are engineering. As a Senior Software Engineer (Measurement and Bring-up), you will partner closely with the Measurement team to implement the test, characterization, calibration, and tuning routines in software—shaping how the software is structured and how the instruments rack is orchestrated to deliver robust, fast, and correct execution in the lab. This is a unique opportunity to contribute to Microsoft’s Quantum Program, dedicated to building a scalable quantum computer to tackle humanity’s most complex challenges. You’ll help make the quantum machine operable as it scales by turning characterization and bring-up needs into dependable software—connecting sophisticated instrumentation to clear, repeatable workflows that accelerate learning cycles in the lab, as well as into robust qubit chip bring-up software for the quantum machine. At Microsoft Quantum, we aim to empower science and scientists to solve the world’s biggest problems by realizing advanced computing platforms at the intersection of high-performance computing, artificial intelligence, and quantum information technology. Microsoft Quantum will change the world of computing and help solve some of humankind’s currently unsolvable problems.
Job Responsibility:
Work with the Measurement team to implement and maintain measurement, characterization, and bring-up routines for qubit devices—turning experimental intent into robust, repeatable software workflows used in the lab and in the quantum machine
Develop Python software that controls and coordinates a complex instruments rack (timing, triggering, waveform generation, acquisition, and metadata capture) to execute high-fidelity experiments reliably and safely
Partner with scientists and engineers to translate user stories into requirements
propose designs that fit the larger bring-up architecture and iterate based on feedback from day-to-day lab usage
Build reusable building blocks (drivers/wrappers, experiment templates, calibration primitives, analysis utilities, configuration/schema models) that enable rapid development of new routines
Ensure measurement data is high quality and traceable: consistent metadata, validation, versioning, and reproducible analysis pipelines
Contribute to software engineering best practices: code reviews, testing, CI/CD, packaging, documentation, and on-call/triage support as needed in a fast-moving environment
Troubleshoot end-to-end issues across software and hardware boundaries (instrument communications, timing, signal integrity symptoms reflected in data) and make clear trade-offs between rapid bring-up and long-term robustness
Requirements:
Doctorate in Computer Science, Software Engineering, Mathematics, Physics, Physical Sciences, or related field AND 1+ year(s) software industry experience, including research and/or development of commercial software, compilers, scientific computing applications, or multi-component systems OR Master's Degree in Computer Science, Software Engineering, Mathematics, Physics, Physical Sciences, or related field AND 3+ years software industry experience, including research and/or development of commercial software, compilers, scientific computing applications, or multi-component systems OR Bachelor's Degree in Computer Science, Software Engineering, Mathematics, Physics, Physical Sciences, or related field AND 4+ years software industry experience, including research and/or development of commercial software, compilers, scientific computing applications, or multi-component systems OR equivalent experience
4+ years programming experience in related programming languages
4+ years experience in a collaborative environment
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
Microsoft Cloud Background Check
Citizenship Verification
Ability to leverage AI tools to drive innovation and efficiency
Nice to have:
Doctorate in Computer Science, Software Engineering, Physics, Electrical Engineering, or related field AND 2+ years software industry experience OR Master's Degree in a related field AND 4+ years software industry experience OR Bachelor's Degree in a related field AND 6+ years software industry experience
2+ years of prior experience building software for qubit (or closely related) test, characterization, calibration, or bring-up routines, including hands-on work with lab instrumentation and measurement workflows
Experience with instrumentation control and lab automation frameworks (e.g., QCoDeS or similar), including driver development and integration with vendor SDKs
Experience developing software that interacts with sophisticated hardware (instrument racks, RF/microwave equipment, digitizers, AWGs, DC sources, cryogenic/facility sensors, or similar), including debugging communications, timing/triggering, and reliability issues
solid grasp of language idioms and the standard library
experience with the scientific Python stack (e.g., NumPy, SciPy, pandas, xarray) and typed/data-modeling approaches (e.g., pydantic)
Familiarity with modern development operations and tooling such as CI&CD on platforms like GitHub and Azure DevOps, and Python tooling (pip/uv, ruff, pre-commit, packaging and dependency management)
Experience designing experiment abstractions, configuration systems, and data/metadata schemas for traceable measurement at scale
Experience with scientific data analysis pipelines, statistical methods, optimization/fitting, and uncertainty quantification applied to device characterization
Experience improving engineering quality in research environments (test strategies for hardware-interfacing code, simulation/mocking of instruments, reliability engineering)
Collaborative engineering experience working with other software developers on shared codebases: design discussions, code reviews, feature ownership, and incorporating feedback from both peers and end users
Strong analytical and problem-solving skills, including comfort working under time pressure and making pragmatic decisions balancing speed, quality, and robustness
Customer obsession: demonstrated ability to distil requirements from user stories, fit requests into a larger architecture, deliver iteratively, and communicate trade-offs clearly
Familiarity with observability/telemetry and data platforms used for debugging large experimental systems (structured logging, time-series data, Kusto/Azure Data Explorer, or equivalent)