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
- Adaptable 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