Ready to push the boundaries of what’s possible with AI? Join a Quantum AI trailblazer on a mission to make AI faster, greener, and more accessible. You’ll collaborate with world-leading experts in quantum computing and AI, building breakthrough solutions that deliver real-world impact for global clients.

This is your chance to work on cutting-edge projects at the intersection of LLMs, quantum-inspired tech, and applied AI innovation.

This is a 9-month fixed-term contract (with potential extension), based in Madrid with hybrid working flexibility.

What you’ll be doing

• Invent new ways to compress and optimise Large Language Models with quantum-inspired methods.
• Benchmark, stress-test, and fine-tune LLMs to boost accuracy, efficiency, and robustness.
• Build and deploy LLM-powered apps – from RAG systems to AI agents.
• Act as an LLM specialist, spotting opportunities where quantum AI can make the impossible possible.
• Design and train custom deep learning models, not just for language, but also in computer vision and beyond.
• Keep experiments transparent with clear documentation, while driving innovation at speed.
• Mentor teammates, share knowledge, and help grow a culture of technical excellence.
• Stay ahead of the curve with the latest research, tools, and breakthroughs in AI.

What we’re looking for

• A degree in AI, Computer Science, Data Science (BSc, MSc, or PhD).
• 2+ years of hands-on deep learning experience – designing, training, or fine-tuning transformers or vision models.
• Strong track record with transformer models (Hugging Face Transformers, Accelerate, Datasets, etc.).
• Solid grasp of deep learning theory, training & inference.
• Excellent Python skills with PyTorch + Hugging Face expertise.
• Understanding of GPU architectures and LLM infrastructure.
• Hands-on with AWS (or similar), Docker, and deploying models in production.
• Problem-solver with sharp debugging, testing, and performance optimisation skills.
• Clear communicator, great collaborator, fluent in English.
• Bonus points for published research in AI/deep learning.