Senior Quantum Software Engineer - Bring-up Software Infrastructure
Description
Overview
Microsoft Quantum has assembled a talented and diverse international team to build the world’s first scalable quantum computer. The research and development 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 Quantum Software Engineer - Bring-up Software Infrastructure , you will partner closely with the Measurement team to implement complex scalable bring-up, calibration, and tuning routines in software—shaping how the software infrastructure is structured to deliver robust, fast, and correct execution in the quantum machine and in the lab contexts.
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. For more information about our team, visit https://www.microsoft.com/en-us/quantum .
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
You will work closely with quantum device characterization experts, experimental and theoretical physicists, and diverse software teams who work across multiple quantum labs on scalable bring-up for the quantum machine. You will collaborate with the Measurement team to translate scalable bring-up and tuning routines into high-quality software: aligning on APIs and abstractions, mapping requirements to the larger bring-up stack, implementing scheduling with concurrency and parallelism while taking into account measurement and device resources as well as overlap bring-up latencies and performance. You will deliver features end-to-end—implementation, testing, documentation, operationalization, and iteration based on user feedback—making pragmatic trade-offs under time pressure while maintaining code quality and long-term maintainability.
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—delivering robust qubit chip bring-up software for the quantum machine as well as repeatable workflows that accelerate learning cycles in the lab.
Responsibilities
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Work with the Measurement team to implement software infrastructure for scalable qubit bring-up routines—turning experimental intent into scalable, efficient, robust, repeatable implementations that run reliably in the quantum machine.
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Develop Python software that controls and coordinates a complex bring-up, calibration, tuning routines and their steps to execute high-fidelity measurements on qubit chips reliably and safely.
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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.
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Build and contribute to infrastructural software components (e.g. scheduler, resource model, concurrency and parallelism primitives), and reusable building-blocks/steps of the bring-up routines that enable rapid development of new routines.
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Ensure measurement data is high quality and traceable: consistent metadata, validation, versioning, and reproducible analysis pipelines.
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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.
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Troubleshoot end-to-end issues across software boundaries (e.g. bad weather scenarios, corner cases, scheduling conflicts, dead-locks) and make clear trade-offs between rapid development and long-term robustness.
- Embody our culture and values.
Qualifications
Required Qualifications
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Master's Degree in Computer Science, Software Engineering, Physics, Electrical Engineering, or related field AND software industry experience
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OR Bachelor's Degree in Computer Science, Software Engineering, Physics, Electrical Engineering, or related field AND solid software industry experience
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OR equivalent experience.
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Experience implementing highly concurrent systems, coordinating large numbers of independent and dependent operations while respecting resource e.g., resource-aware concurrency, scalable execution engines, task scheduling systems, workflow orchestration frameworks, low-latency distributed systems; using Python asyncio, Trio, .NET Tasks, Go goroutines, Rust async, or equivalent technologies; experience with debugging execution flows, timing/triggering, dead-locks, starvation, and reliability issues.
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Proven Python software engineering skills: writing maintainable, testable code; solid grasp of language idioms and the standard library; experience with the scientific Python stack (e.g., NumPy, SciPy, pandas, xarray) and typed/data-modelling approaches (e.g., pydantic).
- Experience designing data pipelines for workflow orchestration, e.g. schemas for data and metadata schemas, provenance, traceability, discoverability.
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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.
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Customer obsession: demonstrated ability to distil requirements from user stories, fit requests into a larger architecture, deliver iteratively, and communicate trade-offs clearly.
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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).
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Demonstrated analytical and problem-solving skills, including comfort working under time pressure and making pragmatic decisions balancing speed, quality, and robustness.
Preferred Qualifications
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Doctorate in Computer Science, Software Engineering, Physics, Electrical Engineering, or related field AND software industry experience
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OR Master's Degree in a related field AND solid software industry experience
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OR Bachelor's Degree in a related field AND in-depth software industry experience
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Prior experience building software for qubit (or closely related) test, characterization, calibration, or bring-up routines; hands-on work with lab instrumentation and measurement workflows is preferred.
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Experience designing experiment abstractions, configuration systems, and data/metadata schemas for traceable measurement at scale.
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Experience with scientific data analysis pipelines, statistical methods, optimization/fitting, and uncertainty quantification applied to device characterization.
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Experience improving engineering quality in research environments (test strategies for hardware-interfacing code, simulation/mocking of instruments, reliability engineering).
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Familiarity with observability/telemetry and data platforms used for debugging large experimental systems (structured logging, time-series data, Kusto/Azure Data Explorer, or equivalent).
Other requirements
- Ability to leverage AI tools to drive innovation and efficiency (e.g., research gathering, day to day tas