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LLM Engineer - zaragoza

hace 1 día

Zaragoza

LLM Engineer (Mid-Senior) Location: Several options within Spain We are partnering with a well-funded, rapidly scaling deep-tech company operating at the intersection of advanced AI and next-generation computing to find their next Senior LLM Engineer. Backed by strong commercial traction and global enterprise clients, the company is building highly efficient, production-grade AI systems designed to solve complex real-world problems at scale. Their team combines world-class researchers and engineers working on cutting-edge challenges in large-scale model development, optimization, and deployment. This is an opportunity to join a highly technical environment where you will directly contribute to the future of large language models - not just apply them. As a Senior LLM Engineer, you will design, train, and optimize large-scale transformer models, contributing across pretraining, post-training alignment (SFT, RLHF, DPO), evaluation, and inference optimization. This is a deeply technical role focused on core model development rather than downstream application or prompt engineering. Key Responsibilities • Design and train transformer-based models from scratch, including large-scale pretraining pipelines, • Contribute to post-training workflows such as SFT, RLHF, and DPO, • Build and optimize large-scale data pipelines for training and evaluation, • Improve model performance through architecture, training, and efficiency optimizations, • Optimize inference and training performance across GPU/HPC environments, • Collaborate with engineering teams to deploy models into production systems, • Mentor junior engineers and contribute to technical best practices Required Experience & Skills • 2+ years of hands-on experience training transformer or LLM models from scratch, • 5+ years overall experience for Senior-level candidates across deep learning applications, • Strong understanding of transformers, optimization, and deep learning fundamentals, • Expertise in Python, PyTorch, and the Hugging Face ecosystem, • Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron, • Familiarity with inference optimization tools such as vLLM or TensorRT-LLM, • Experience working with large datasets, scalable training pipelines, and GPU optimization Why Apply? • Work on true LLM innovation, not just downstream applications, • Influence next-generation AI systems at scale, • Join a highly technical, research-driven environment with real-world impact, • Competitive compensation, flexible working, and strong growth potential Recruiter’s Note We are specifically targeting engineers who have built and optimized models themselves—not candidates focused purely on prompt engineering or API-based LLM usage. If you have contributed to large-scale training pipelines, model optimization, or architecture-level improvements, we would like to hear from you. Apply now or send a copy of your CV, referencing the title and location, and with a short intro to . By applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our Privacy Notice ()

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