Machine Learning Engineer

Machine Learning Engineer | AI Start-up | 9-Month fixed-term Contract

Join a European deep-tech leader in quantum and AI.

A well-funded, fast-growing company backed by major global investors with its groundbreaking technology is already transforming AI, compressing large language models by up to 95% and cutting inference costs by 50–80%.

This is your chance to be part of a team often described as a “quantum-AI unicorn in the making.”

This is a Hybrid opportunity working out of Zaragoza.

What You'll Do :

You'll design and develop new techniques to compress Large Language Models using quantum-inspired technologies. You'll build LLM-based applications like RAG and AI agents, and you'll assess, fine-tune, and optimize models for enhanced performance and efficiency. As a domain expert, you'll identify opportunities for quantum AI-driven innovation and deliver custom deep-learning models for our clients.

Who We're Looking For :

• Experience : A Bachelor's, Master's, or Ph.D. in AI, Computer Science, or a related field. You should have at least 2 years of hands-on experience designing, training, or fine-tuning deep learning models, with a strong command of libraries such as HuggingFace Transformers.
• Technical Skills : You need a solid theoretical understanding of deep learning algorithms and neural networks, as well as excellent Python programming skills. Experience with cloud platforms (ideally AWS), containerization (Docker), and deploying AI solutions in a cloud environment is essential. You should also have a strong understanding of GPU architectures and LLM hardware / software infrastructures.
• Collaboration : Excellent communication skills and the ability to work collaboratively in a fast-paced team environment. You'll participate in code reviews and help mentor junior team members.
• Preferred : Experience with large-scale workloads in HPC clusters, inference and deployment environments (TensorRT, vLLM), building and evaluating RAG systems, and familiarity with MLOps.

Perks & Benefits :

Interested? Apply directly through LinkedIn, or send your CV to

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