A leading European deep-tech company in AI and quantum technologies is looking for a talented Deep Learning Engineer to join their team on a fixed-term contract ending June 2026.This is an exciting opportunity to work on cutting-edge AI and LLM compression—reducing model sizes by up to 95% while cutting inference costs by 50–80%—impacting real-world AI deployments globally.What’s on Offer:Competitive annual salarySigning bonus at incorporation + retention bonus at contract completionRelocation package if neededHybrid work: 3 days in-office, 2 days remoteFlexible working hoursInternational, multicultural environmentFast-growing, Series B backed company at the forefront of deep techRole Responsibilities:Design, train, and optimize LLMs and computer vision models end-to-endApply and develop state-of-the-art model compression techniques (pruning, distillation, quantization, low-rank decomposition)Build reproducible pipelines for large-model compression and evaluationConduct fine-tuning, empirical studies, and benchmark analysis for real-world deploymentCollaborate with cross-functional teams to integrate compressed models into productionRequired Experience:Master’s or Ph.D. in Computer Science, Machine Learning, EE, Physics, or related field3+ years hands-on experience training deep learning models from scratchExpertise in model compression techniques and foundational architectures (CV & LLMs)Strong Python & PyTorch skills; familiarity with HuggingFace, Lightning, DeepSpeed, or equivalentExperience with large-scale distributed training and optimizing models for deploymentPreferred:Ph.D. with focus on efficient deep learning, compression, sparsity, NASOpen-source contributions in ML/compression toolsExperience with hardware-aware model optimizationLocations: Madrid, Zaragoza, Barcelona (Hybrid)Contract: Fixed-term until June 2026