Machine Learning Engineer
European Tech Recruit
Municipality of Zaragoza, Spain
2 days ago
Role details
Contract type
Temporary contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Experience level
IntermediateJob location
Municipality of Zaragoza, Spain
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Computer Vision
Software Debugging
Python
Machine Learning
Quantum Computing
PyTorch
Large Language Models
Deep Learning
Information Technology
HuggingFace
Docker
Job description
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 fixed-term contract until end of June 2026 (with potential extension), based in Barcelona 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.
Requirements
- 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.