Software Engineer - Bring-up Software Infra.

Microsoft

Job Description

Job Title: Senior Quantum Software Engineer - Bring-up Software Infrastructure. Location:

Kongens Lyngby, Copenhagen, Denmark
Hybrid, 3 days per week in office
Travel: Less than 25%

Responsibilities:

Develop software infrastructure for scalable qubit bring-up routines in collaboration with the Measurement team.
Develop Python software to control and coordinate bring-up, calibration, and tuning routines for high-fidelity qubit measurements.
Translate experimental requirements and user stories into scalable software designs;
Build infrastructure components including schedulers, resource models, concurrency and parallelism primitives, and reusable bring-up routine components.
Design software that respects measurement and device resources while managing overlapping bring-up latencies and performance.
Ensure measurement data has consistent metadata, validation, versioning, traceability, and reproducible analysis pipelines.
Deliver software features end-to-end, including implementation, testing, documentation, operationalization, and iteration based on user feedback.
Contribute to code reviews, testing, CI/CD, packaging, documentation, and on-call or triage support.
Troubleshoot issues across software boundaries, including corner cases, scheduling conflicts, deadlocks, and reliability problems.
Make pragmatic trade-offs between rapid development, software quality, and long-term maintainability;
Collaborate with quantum device characterization experts, experimental and theoretical physicists, and software teams across multiple quantum laboratories.
Contribute to software that enables repeatable workflows and faster learning cycles in quantum laboratories.

Qualifications:

Master's degree in Computer Science, Software Engineering, Physics, Electrical Engineering, or a related field plus software industry experience, or equivalent experience.
Bachelor's degree in a related field plus solid software industry experience is also accepted.
Experience implementing highly concurrent systems that coordinate large numbers of independent and dependent operations while respecting resources.
Experience with scalable execution engines, task scheduling systems, workflow orchestration frameworks, low-latency distributed systems, or similar technologies.
Experience with concurrency technologies such as Python asyncio, Trio, .NET Tasks, Go goroutines, Rust async, or equivalent.
Experience debugging execution flows, timing and triggering issues, deadlocks, starvation, and reliability problems;
Strong Python software engineering skills, including maintainable and testable code, language idioms, and the standard library.
Experience with the scientific Python ecosystem, including NumPy, SciPy, pandas, or xarray.
Experience with typed or data-modeling approaches such as pydantic.
Experience designing workflow data pipelines, including data schemas, metadata, provenance, traceability, and discoverability.
Experience collaborating with software developers on shared codebases through design discussions, code reviews, feature ownership, and user feedback.
Ability to translate user stories into requirements, fit requests into larger architectures, deliver iteratively, and communicate technical trade-offs.
Familiarity with CI/CD using platforms such as GitHub and Azure DevOps;
Familiarity with Python development tooling such as pip/uv, ruff, pre-commit, packaging, and dependency management.
Strong analytical and problem-solving skills and the ability to make pragmatic decisions under time pressure.

Preferred:

Doctorate in Computer Science, Software Engineering, Physics, Electrical Engineering, or a related field plus software industry experience.
Prior experience building software for qubit testing, characterization, calibration, or bring-up routines.
Hands-on experience with laboratory instrumentation and measurement workflows;
Experience designing experiment abstractions, configuration systems, and data or metadata schemas for traceable measurements at scale.
Experience with scientific data analysis pipelines, statistical methods, optimization, fitting, and uncertainty quantification for device characterization.
Experience improving software engineering quality in research environments, including hardware-interface testing and simulation or mocking of instruments.
Familiarity with observability and telemetry for large experimental systems, including structured logging, time-series data, Kusto, Azure Data Explorer, or equivalent platforms.

Other Requirements:

Ability to use AI tools for innovation, research gathering, and day-to-day task automation.
Must meet Microsoft, customer, and/or government security screening requirements.
Must pass the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
The role may involve access to export-controlled information under regulations including ITAR, EAR, EU Dual Use Regulation, or other applicable regulations.
Citizenship or qualifying residency status must be verified where required for access to export-controlled information;
Lawful permanent residents, refugees, and asylees may verify their status using applicable documentation.
Applications are accepted on an ongoing basis until the position is filled.

Salary: