Quantum Engineer, Calibration Automation

Entangled Future; Espoo; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

IQM Quantum Computers in Espoo, Finland seeks a Quantum Engineer for Calibration Automation to join the Engineering team in hardware engineering. This mid-level, full-time role focuses on calibration strategies for QPU hardware and software tooling.

You will contribute to scalable calibration graphs, experiment planning, and cross-disciplinary collaboration across physics, software, and hardware engineering to advance the quantum ecosystem.

Qualifications

• Master's or PhD in Physics or Quantum Engineering, or equivalent experience.
• Experience calibrating quantum systems of any architecture.
• Excellent Python software development skills with version control and testing.
• Ability to plan, execute, and analyze experiments independently.
• Strong analytical and problem-solving skills.
• Good communication skills and ability to work across teams.

Responsibilities

• Contribute to improved calibration logic development and scalable calibration graphs.
• Develop calibration graphs for initial calibration and recalibration of a quantum computer.
• Collaborate across physics, software, and quantum hardware engineering to advance calibration methods.

Skills

Python programming

Software engineering

Analytical thinking

Communication

Education

Master's or PhD in Physics or Quantum Engineering

Job description

Quantum Engineer, Calibration Automation at IQM Quantum Computers, Espoo, FI. A mid-level full time position in the Engineering team, listed under hardware engineering.

We 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 do

Your 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.

Why IQM?

• 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.

The future of computing won’t build itself. You might be one of the few who do.

• 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. 600M€+ Total Funding | 400+ Team Members | 30+ Quantum Computers Built | 300+ Patents Filed | 10 Location Globally

Requirements

• Master'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

• 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.