At IQM, we build world-leading quantum computers for the well-being of humankind. We design systems to tackle computational challenges beyond the practical limits of classical machines. Our work sits at the edge of science and engineering. It's complex, demanding, and deeply collaborative. We turn deep research into reliable, full-stack systems that drive discoveries in fields like medicine, energy, and technology, reshaping how the world computes.
Join the team that gives quantum a heartbeat.
The workWe are looking for a quantum engineer joining our mission to establish better and better calibration and recalibration strategies of a QPU. You will be part of the Calibration Automation team, which developed a graph-based calibration framework and corresponding calibration graphs for, e.g., initial calibration and recalibration of a quantum computer.
What you’ll actually doYour role is to contribute to an improved calibration logic development, scalable calibration graph development, and calibration development for future chip architectures. This is a unique opportunity to work at the intersection of experimental physics, software development, and quantum hardware engineering.
What we’re looking forMaster's or PhD in Physics or Quantum Engineering, or equivalent experience in a related field.
Experience in calibrating quantum systems of any architecture. Examples include experience calibrating single-qubit gates, two-qubit gates, readout, or other relevant quantum operations.
Excellent software development skills in Python and best practices in software engineering (e.g. version control, testing, code review).
Ability to plan, execute, and analyze experiments independently.
Strong analytical and problem-solving skills.
Good communication skills and ability to work across teams.
Nice to have skills
Data analysis skills (e.g. time-series analysis).
Experience with machine learning modeling, including training and deploying models in production.
Understanding of high-performance computing and parallelization techniques for numerical calculation and data processing.
Understanding of advanced statistical methods and decision-making techniques (e.g. Bayesian optimization, reinforcement learning, etc.).
Experience with AI tooling, such as AI harnessing for scientific and engineering tasks.
Full-stack quantum computing: From quantum hardware to software layers and beyond, we build across the full-stack.
High-performance playground: We aim high, and we know sustainable performance only works when life outside work does too—hybrid setups, flexible hours.
Never the smartest: Expect to learn constantly. You won't always be the smartest person in the room, and that's the point.
Approachable leadership: Flat hierarchy, direct access. Feel free to approach any leaders. They're friendlier than they look!
The sweet spot: Big enough to matter. Small enough to move fast. Growing between a startup and a corporation. We’re in the phase where top performers get noticed.
Bigger than IQM: Our people build know-how for the entire quantum ecosystem. We publish papers, run hackathons, and help shape a market that's still being defined.
Meet our people and learn more about IQM on our stories page.
Explore our scientific publications.
We'll start interviews and move forward with hiring as soon as we meet strong candidates. Please submit your application soon.
600M€+ Total Funding | 400+ Team Members | 30+ Quantum Computers Built | 300+ Patents Filed | 10 Location Globally
Skills Required
- Master's or PhD in Physics or Quantum Engineering, or equivalent experience in a related field.
- Experience in calibrating quantum systems (single-qubit gates, two-qubit gates, readout, or other quantum operations).
- Excellent software development skills in Python and best practices (version control, testing, code review).
- Ability to plan, execute, and analyze experiments independently.
- Strong analytical and problem-solving skills.
- Good communication skills and ability to work across teams.
- Data analysis skills (e.g., time-series analysis).
- Experience with machine learning modeling, including training and deploying models in production.
- Understanding of high-performance computing and parallelization techniques.
- Understanding of advanced statistical methods and decision-making techniques (e.g., Bayesian optimization, reinforcement learning).
- Experience with AI tooling for scientific and engineering tasks.
What We Do
IQM builds superconducting full‑stack quantum computers and cloud services for research institutions, HPC centers, enterprises and national labs. The company delivers on‑premises systems and managed cloud access, focusing on scalable, high‑fidelity qubit architectures and full‑stack control to accelerate real‑world applications and research in science, industry and technology.
