Senior Large Language Models Engineer

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AI Summary

Design and develop Large Language Models using transformer models and quantum-inspired approaches. Collaborate with research and engineering teams to improve model performance and scalability in real-world applications. Contribute to the wider direction of AI development within the organization.

Key Highlights
Work on cutting-edge problems combining Large Language Models with novel approaches
Collaborate with research and engineering teams
Contribute to the wider direction of AI development
Key Responsibilities
Design and develop techniques to compress and optimize LLMs using quantum-inspired approaches
Evaluate model performance, running benchmarks, and identifying areas for improvement
Fine-tune and enhance models for accuracy, robustness, and efficiency
Support and mentor junior engineers
Contribute to code reviews and best practices
Technical Skills Required
Large Language Models Transformer Models PyTorch Deep Learning Neural Networks GPU Architectures AWS Docker HuggingFace
Benefits & Perks
Visa sponsorship
Relocation package
Hybrid work model
Nice to Have
RAG systems
TensorRT
vLLM
HPC or large-scale training environments
Exposure to MLOps or DevOps practices
Research background or publications in deep learning

Job Description


Senior LLM Engineer - Large Language Models / Transformer Models / Deep Learning / PyTorch


We're currently supporting an organization at the forefront of AI and quantum-inspired technologies, and they're looking to bring in both Mid and Senior level LLM Engineers to join their growing team.

This is a great opportunity to work on genuinely cutting-edge problems, combining Large Language Models with novel approaches to improve performance, efficiency, and scalability across a range of real-world applications.


The role:

You’ll be working closely with research and engineering teams to design, build, and optimise LLMs, while contributing to the wider direction of AI development within the business.

This is a permanent position, working on a hybrid model, in the Basque Country of northern Spain.


What will you do?

  • Design and develop techniques to compress and optimise LLMs using quantum-inspired approaches
  • Evaluate model performance, running benchmarks, and identifying areas for improvement
  • Fine-tune and enhance models for accuracy, robustness, and efficiency
  • Act as a subject matter expert for LLM-related challenges and opportunities
  • Collaborate with cross-functional teams to integrate models into production systems
  • Support and mentor junior engineers
  • Contribute to code reviews and best practices
  • Keep up with the latest advancements in LLM and NLP research


What they're looking for:

For Mid level:

  • 3+ years experience working with transformer models and LLMs

For Senior level:

  • 5+ years experience across deep learning, including transformers and ideally other domains such as computer vision

For both:

  • Strong Python skills with frameworks such as PyTorch and HuggingFace
  • Solid understanding of deep learning theory and neural networks
  • Experience developing training models / building LLM’s from scratch
  • Good understanding of GPU architectures and performance optimisation
  • Experience with AWS, Docker, and deploying models in cloud environments
  • Strong problem-solving and communication skills


Bonus points for:

  • Experience with RAG systems, TensorRT, vLLM, or similar inference tools
  • HPC or large-scale training environments
  • Exposure to MLOps or DevOps practices
  • Research background or publications in deep learning
  • Spanish language skills


Visa sponsorship for Spain can be facilitated, so international applicants are encouraged


If you’re interested in working at the intersection of advanced AI and emerging technologies, and want to have real impact on next-generation LLM systems, feel free to reach out or apply directly.


If this sounds interesting and you'd like to learn more, click the link below to apply or email me with a copy of your CV on smouland@eu-recruit.com


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