Machine Learning Engineer - LLM / Fixed Term Contract

• Build data and model pipelines end-to-end - from dataset creation, sourcing, and validation to training and deployment.
• Design rigorous evaluation frameworks to test performance, reliability, and model alignment.
• Scale and optimize training/inference processes for speed, efficiency, and performance.
• Improve post-training models using supervised fine-tuning and reinforcement learning methods.
• Apply model compression and optimization techniques to meet latency and footprint goals.
• Collaborate with research and software engineering teams on data curation, model serving, and system observability.
• Write clean, well-tested Python code while maintaining documentation and engineering standards.

• Proficiency in Python and the modern ML stack (e.g., PyTorch, NumPy, Pandas).
• Solid understanding of large language model (LLM) training, evaluation, and data strategies.
• Experience handling large-scale datasets - collection, filtering, and annotation.
• Strong grasp of GPU computing, containerization (Docker), and workflow orchestration.

Keywords: Machine Learning / ML Engineer / AI Engineer / Quantum AI / Large Language Models / LLM / PyTorch / Python / Data Pipelines / Model Optimization / Reinforcement Learning / Distributed Systems / GPU Computing / Docker / ML Infrastructure / Data Engineering / Model Evaluation / AI Product Development

We are currently partnered with a world-leading quantum AI company developing cutting-edge solutions that make artificial intelligence faster, greener, and more accessible. Their products bridge the gap between quantum computing and AI, helping global clients solve complex real-world problems at scale. This is a fixed-term contract with hybrid working in Zaragoza.