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 work
We are looking for a Senior Quantum Algorithms Engineer to join our Quantum Machine Learning (QML) team. This position strengthens IQM’s leadership across the stack by advancing quantum machine learning methods and integrating them into real-world computational workflows. As part of the algorithms and applications department, the machine learning team assess, develop and improve quantum machine learning algorithms with the goal of understanding and expanding where quantum computers provide advantage; whether in terms of samples required, algorithm run time, or final predictive performance.
We design with the device in mind, incorporating circuit structure, measurement strategy, error-mitigation and correction, using in-house expertise and real hardware implementations to guide our strategy. With this, we aim to deliver meaningful quantum machine learning methods, that do not just satisfy theoretical guarantees but also can be impactful in practice.
This position is based in Munich, Germany, although remote work may be considered. The team is distributed across Germany, France, and Finland.
Designing novel quantum machine learning algorithms for early fault-tolerant quantum computers.
Assessing via detailed resource estimation algorithm efficiency, incorporating analysis from theoretical results, input from hardware and device characterisation teams, simulated and real hardware experiments.
Development of resource reduction schemes ranging from improved transpilation techniques and exploiting hardware-specific knowledge to improved algorithm design and incorporation of classical resources.
Strategic assessment of new and current algorithmic proposals, considering in detail required resources for implementation, valuation of application areas, and competing classical approaches.
Incorporating the research of the quantum error correction (QEC) teams into algorithm design and shaping the requirements for the next generation of devices.
Driving the publication of high-impact research papers, presenting at scientific conferences, and promoting results through networking and collaboration.
Contributing to intellectual property via the filing of patents, producing technical reports, comprehensive documentation, and educational content.
Leading collaborations with industry and academic partners, as well as internal with hardware, software, and research teams, with a focus on impact and delivering results.
Mentoring team members through knowledge sharing, both technical and soft skills.
Explaining and translating technical content for business partners, collaborators and clients.
Ph.D. in theoretical physics, computer science, mathematics, or a related field, or demonstrably equivalent experience.
At least 3 years in a postdoctoral or an equivalent industrial position, demonstrating individual research and mentorship capabilities.
A track record of impactful publications in quantum machine learning.
Strong background in quantum computing, quantum information, and classical computer science, including algorithm design, complexity and machine learning theory.
Expert knowledge of quantum algorithms, including quantum signal processing, quantum phase estimation, linear combination of unitaries and amplitude amplification, as well specific quantum machine learning knowledge (e.g. Born machines, QRAM design, quantum kernels/ feature maps).
Strong analytical, mathematical modelling, and problem-solving skills.
Proficiency with python, quantum programming frameworks (e.g., Qiskit, Cirq, Qrisp) as well as standard software development practices (git/Github/Gitlab, unit testing, code clarity + standardisation).
An ability to communicate complex technical concepts and results to audiences ranging from non-technical to experts in the field.
Experience in leading collaborations, as well as providing technical contributions to cross-discipline projects.
Knowledge of quantum error correction and superconducting architectures.
Non-asymptotic resource estimation of either scalable or fault-tolerant algorithms / quantum gadgets.
Demonstrable experience applying theoretical tools to practical problems, such as classical shadows, MPS/ tensor network approximations, or dynamical Lie algebras.
Experience contributing to or producing mature software libraries, either for open-source or product purposes.
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.
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
