Work Mode: Hybrid (3 days from office, 2 day remote) Job Overview We are seeking a skilled and experienced Machine Learning Engineer with a strong background in Large Language Models to join our team. In this role 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 have the opportunity to work on challenging projects, contribute to cutting-edge research, and shape the future of LLM and NLP technologies. Required minimum

Qualifications:
Bachelor's, Master's or Ph.
D. in Artificial Intelligence, Computer Science, Data Science, or related fields. 5+ years of hands-on experience with designing, training or fine-tuning deep learning models, preferably working with transformer or computer vision models. 5+ year of hands-on experience using 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 and LLM hardware/ software infrastructures. 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 or any tech field is a plus As a Machine Learning Engineer, you will 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. Build LLM based applications such as RAG and AI agents. 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. Design, train and deliver custom deep learning models for our clients Work in diverse areas beyond LLM, e.g., computer vision. Maintain comprehensive documentation of LLM development processes, experiments, and results. Share your knowledge and expertise with the team to foster a culture of continuous learning, guiding junior members of the team in their technical growth and helping them develop their skills in LLM development. Participate in code reviews and provide constructive feedback to team members. Stay up to date with the latest advancements and emerging trends in LLMs and recommend new tools and technologies as appropriate. Perks and Benefits Signing bonus. Relocation package (if applicable). Private health insurance. Eligibility for educational budget according to internal policy. Language classes and discounted lunch options Working in a high paced environment, working on cutting edge technologies.

📌 Machine Learning Engineer (España)
🏢 RemoteStar
📍 España