We are a European deep-tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide — compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50–80%.
Joining us means working on cutting-edge solutions that make AI faster, greener, and more accessible — and being part of a company often described as a “quantum-AI unicorn in the making.”
Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.
Relocation package (if applicable).
Fixed-term contract ending in June 2026.
Hybrid role and flexible working hours.
As a Machine Learning Engineer, you will
Design and develop new techniques to compress Large Language Models based on quantum-inspired technologies to solve challenging use cases in various domains.
Conduct rigorous evaluations and benchmarks of model performance, identifying areas for improvement, and fine-tuning and optimising LLMs for enhanced accuracy, robustness, and efficiency.
Use your expertise to assess the strengths and weaknesses of models, propose enhancements, and develop novel solutions to improve performance and efficiency.
Act as a domain expert in the field of LLMs, understanding domain-specific problems and identifying opportunities for quantum AI-driven innovation.
Share your knowledge and expertise with the team to foster a culture of continuous learning, guiding junior members of the team in their technical growth and helping them develop their skills in LLM development.
Bachelor's, Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.
~2+ years of hands-on experience with designing, training or fine-tuning deep learning models, preferably working with transformer or computer vision models.
~Solid mathematical foundations and theoretical understanding of deep learning algorithms and neural networks, both training and inference.
~ Excellent problem-solving, debugging, performance analysis, test design, and documentation skills.
~ Strong understanding with the fundamentals of GPU architectures and and LLM hardware/ software infrastructures.
~ Excellent programming skills in Python and experience with relevant libraries (PyTorch, HuggingFace, etc.).
~ Experience with cloud platforms (ideally AWS), containerization technologies (Docker) and with deploying AI solutions in a cloud environment
~ Fluent in English
Experience running large-scale workloads in high-performance computing (HPC) clusters.
Experience in handling large datasets and ensuring data quality.
Experience with inference and deployment environments (TensorRT, vLLM, etc.).
computer vision, audio or signal processing.
Experience in DevOps/MLOps practices in deep learning product development.