Machine Learning Engineer (Product)
We are working with a leading Quantum AI start-up taking on a mission to make AI faster, greener, and more accessible. Within this role you will be collaborating 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.Keywords : Machine Learning / GPU / LLM / Large Language / Deep Learning / AWS / Orchestration / Docker / Mistral AI / OpenAI / LangChain / TPU / Hugging Face / PyTorch / Transformer Models / Fine-Tuning
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