AI/ML Engineer (Quantum Computing)

Location: Delft, Netherlands — hybrid

Salary: €70,000–€90,000 per year, depending on experience

Company

hirify.global develops quantum error correction technology and collaborates with quantum hardware providers and government agencies to advance fault-tolerant quantum computing.

What you will do

• Design, train and evaluate machine learning models for quantum error correction tasks, including decoding, calibration and noise characterisation, using simulated and experimental data.
• Build data pipelines and training infrastructure for experimentation and hyperparameter tuning.
• Optimise models for performance, latency and scalability under hardware and QEC constraints.
• Work with QEC researchers to develop practical ML prototypes and algorithms.
• Integrate models into hirify.global’s QEC stack with software, hardware and product teams.
• Communicate results through technical documentation, discussions, publications and conference presentations where appropriate.

Requirements

• MSc or PhD in Computer Science, Mathematics, Physics or a related technical field, or equivalent professional experience.
• At least 2–3 years of experience in machine learning, deep learning or other AI areas, gained in industry or academia.
• Working knowledge of quantum error correction.
• Strong programming skills, preferably in Python and/or C++, plus software engineering practices including version control, testing and code review.
• Experience with NumPy, SciPy and ML frameworks such as JAX or PyTorch.
• Understanding of neural network architectures including transformers, CNNs and RNNs, and supervised, unsupervised and reinforcement learning.
• Experience with model design and optimisation, including training, evaluation, fine-tuning and interpretation.
• Experience using GPU or TPU acceleration.
• Excellent communication and collaboration skills, including explaining technical ideas to colleagues from different backgrounds.

Nice to have

• Experience with QEC simulation and decoding tools such as Stim or PyMatching.
• Understanding of qubit modalities such as superconducting, trapped-ion, neutral-atom or photonic systems.
• Experience with GPU-enabled SLURM clusters.
• Knowledge of parallel programming such as CUDA or experience optimising models for low-latency, hardware-constrained deployment.
• Experience applying ML to QEC or quantum computing, demonstrated through publications or open-source contributions.

Culture & Benefits

• Hybrid work in Delft and a diverse environment spanning software and hardware development, quantum information theory, physics and mathematics.
• Annual bonus plan and paid time off.
• Learning and development opportunities, including regular learning events and training and conference budgets.
• Benefits vary by location and typically support wellbeing and financial security.

Hiring process

• Submit a CV and covering letter explaining the motivation for applying and the skills and experience relevant to the role.
• Applications are reviewed on a rolling basis and interviews begin as suitable applications are received; there is no closing date.