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 salary
• Signing bonus at incorporation + retention bonus at contract completion
• Relocation package if needed
• Hybrid work: 3 days in-office, 2 days remote
• Flexible working hours
• International, multicultural environment
• Fast-growing, Series B backed company at the forefront of deep tech

Role Responsibilities:

• Design, train, and optimize LLMs and computer vision models end-to-end
• Apply and develop state-of-the-art model compression techniques (pruning, distillation, quantization, low-rank decomposition)
• Build reproducible pipelines for large-model compression and evaluation
• Conduct fine-tuning, empirical studies, and benchmark analysis for real-world deployment
• Collaborate with cross-functional teams to integrate compressed models into production

Required Experience:

• Master’s or Ph.D. in Computer Science, Machine Learning, EE, Physics, or related field
• 3+ years hands-on experience training deep learning models from scratch
• Expertise in model compression techniques and foundational architectures (CV & LLMs)
• Strong Python & PyTorch skills; familiarity with HuggingFace, Lightning, DeepSpeed, or equivalent
• Experience with large-scale distributed training and optimizing models for deployment

Preferred:

• Ph.D. with focus on efficient deep learning, compression, sparsity, NAS
• Open-source contributions in ML/compression tools
• Experience with hardware-aware model optimization

Locations: Madrid, Zaragoza, Barcelona (Hybrid)

Contract: Fixed-term until June 2026