Descripción de la oferta
Senior LLM Engineers & ResearchersLocation: Barcelona, Madrid, Zaragoza, San Sebastian (on-site with some flexibility)Asegúrese de leer detenidamente la información sobre esta oportunidad antes de presentar su candidatura.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 Engineers & Researchers. Their team combines world-class researchers and engineers working on cutting-edge challenges in large-scale LLM 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 or Researcher, 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 ResponsibilitiesDesign and train transformer-based models from scratch, including large-scale pretraining pipelinesContribute to post-training workflows such as SFT, RLHF, and DPOBuild and optimize large-scale data pipelines for training and evaluationImprove model performance through architecture, training, and efficiency optimizationsOptimize inference and training performance across GPU/HPC environmentsCollaborate with engineering teams to deploy models into production systemsMentor junior engineers and contribute to technical best practicesRequired Experience & SkillsPhD with industry experience since with hands-on experience training transformer or LLM models from scratchStrong understanding of transformers, optimization, and deep learning fundamentalsExpertise in Python, PyTorch, and the Hugging Face ecosystemExperience with distributed training frameworks such as DeepSpeed, FSDP, or MegatronExperience with inference optimization tools such as vLLM or TensorRT-LLMExperience working with large datasets, scalable training pipelines, and GPU optimizationWhy Apply?Work on true LLM innovation, not just downstream applicationsInfluence next-generation AI systems at scaleJoin a highly technical, research-driven environment with real-world impactCompetitive compensation, flexible working, and strong growth potentialRecruiter’s NoteWe are specifically targeting those who have built and optimized models themselves - not those for example who have focused on prompt engineering or API-based LLM usage. If you have contributed to large-scale training pipelines, model optimization, quantization, compression 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 . xcskxlj 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 ( )
