LLM Engineer - (Machine Learning/AI) - Hybrid

Machine Learning Engineer (LLM)

A fantastic opportunity for a driven Machine Learning Engineer to join fast-growing deep-tech company, who provide hyper-efficient software to global companies across finance, energy, manufacturing and cybersecurity to gain an edge with quantum computing and artificial intelligence.

You will have the opportunity to leverage cutting-edge quantum and AI technologies to lead the design, implementation, and improvement of our language models, as well as working closely with cross-functional teams to integrate these models into our products. You will get to work on challenging projects, contribute to cutting-edge research, and shape the future of LLM and NLP technologies.

** Hybrid working from Sites in Madrid, Barcelona, Zaragoza or San Sebastian**

Responsibilities

• Design and develop new techniques to compress Large Language Models based on quantum-inspired technologies to solve challenging use cases in various domains.

• Conduct rigorous evaluations and benchmarks of model performance, identifying areas for improvement, and fine-tuning and optimising LLMs for enhanced accuracy, robustness, and efficiency.

• Use your expertise to assess the strengths and weaknesses of models, propose enhancements, and develop novel solutions to improve performance and efficiency.

• Act as a domain expert in the field of LLMs, understanding domain-specific problems and identifying opportunities for quantum AI-driven innovation.

• Maintain comprehensive documentation of LLM development processes, experiments, and results.

• Participate in code reviews and provide constructive feedback to team members.

Qualifications

• Master's or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or related fields.

• Mid: 2+ years of hands-on experience with designing, training or fine-tuning transformer models.

• Senior: 5+ years of hands-on experience with designing, training or fine-tuning transformer and other deep learning models (e.g. computer vision).

• 2+ year of hands-on experience using LLM and Transformer models, with excellent command of libraries such as HuggingFace Transformers, Accelerate, Datasets, etc."

• Solid mathematical foundations and theoretical understanding of deep learning algorithms and neural networks, both training and inference.

• Excellent problem-solving, debugging, performance analysis, test design, and documentation skills.

• Strong understanding with the fundamentals of GPU architectures. • Excellent programming skills in Python and experience with relevant libraries (PyTorch, HuggingFace, etc.).

• Experience with cloud platforms (ideally AWS), containerization technologies (Docker) and with deploying AI solutions in a cloud environment

• Excellent written and verbal communication skills, with the ability to work collaboratively in a fast-paced team environment and communicate complex ideas effectively.

• Previous research publications in deep learning is a plus.

• Fluent in English.

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