Take a leading role in advancing and scaling up our tensor network research, developing new methods for efficient ML model architectures, training, and optimisation, and pushing them beyond the current state of the art.
Design and train modern deep learning models, with a focus on making large-scale training more efficient.
Develop and improve the algorithms at the core of our methods, taking ideas from concept to validated result.
Work with teams across the division to apply these methods to challenging real-world problems.
Contribute to patents and selected publications, and represent Terra Quantum at leading conferences.
Help structure the team's research and mentor junior colleagues, raising both scientific and engineering standards.
Collaborate with engineers across the division to run methods efficiently on modern computing platforms.

D., or M.Sc. with significant relevant experience, in machine learning, applied mathematics, physics, computer science, or a closely related field, with strong mathematical foundations in linear algebra, numerical methods, optimisation, and probability.
Hands-on experience training modern deep learning models such as transformers, including efficient large-scale training and fine-tuning, using frameworks such as PyTorch or JAX.
Strong command of optimisation methods for machine learning, including gradient-based and large-scale optimisation, regularisation, and training dynamics
Experience with efficient training and model compression techniques, such as low-rank methods, quantisation, distillation, or sparsity.
A demonstrated ability to master new mathematical frameworks quickly: either existing expertise in this area, or a clear track record showing you can pick it up
Strong Python skills and solid software-engineering practice, with experience on GPU and HPC environments and distributed training.
A record of publications or patents, and the ability to take a research direction from concept to result independently.
Strong communication and organisational skills, and the willingness to guide and develop junior colleagues.
Knowledge of tensor networks and related numerical and optimisation (preferred)
Domain exposure to one or more of: finance, chemistry, or operations (preferred)
Knowledge of C++ and familiarity with quantum computing (preferred)

An opportunity to work with some of the brightest minds in the pioneering field of Quantum Technologies as well as an experienced and progressive Leadership team
Gain knowledge of some of the most cutting-edge technology developments in science & engineering
A chance to be part of one of Europe’s leading technology firms of the upcoming decades
Welcoming, friendly, and professional colleagues
A personal development plan with clear goals for advancement
A competitive salary
Flexible working arrangements
A diverse and supportive atmosphere, where innovation and initiative are encouraged

Senior Tensor AI Scientist

Key skills