Machine Learning Engineer

We are looking for a talented and experienced Machine Learning Engineer with expertise in Large Language Models to join our clients team in Spain!

This role offers the opportunity to work with cutting-edge quantum and AI technologies, spearheading the design, implementation, and enhancement of our language models. You will collaborate with cross-functional teams to seamlessly integrate these models into our products, tackle complex challenges, contribute to innovative research, and help shape the future of LLM and NLP technologies.

Responsibilities:

• Develop advanced techniques for compressing Large Language Models using quantum-inspired technologies to address complex problems across various domains.
• Perform rigorous evaluations and benchmarks to assess model performance, identify areas for enhancement, and optimize LLMs for improved accuracy, robustness, and efficiency.
• Leverage your expertise to analyze model strengths and weaknesses, propose improvements, and devise innovative solutions to boost performance and efficiency.
• Serve as a subject matter expert in LLMs, addressing domain-specific challenges and exploring opportunities for quantum AI-driven innovation.
• Maintain detailed documentation of LLM development processes, experiments, and findings.
• Share knowledge within the team, foster continuous learning, mentor junior team members, and support their growth in LLM development.
• Participate in code reviews and offer constructive feedback to peers.
• Stay informed about the latest advancements and trends in LLMs, recommending relevant tools and technologies.

Qualifications:

• A Master’s or Ph.D. in Artificial Intelligence, Computer Science, Data Science, or a related field.
• 3+ years of hands-on experience with deep learning models and neural networks, particularly in working with Large Language Models, Transformer architectures, or computer vision models.
• At least 1 year of practical experience with LLMs and Transformer models, with proficiency in libraries such as HuggingFace Transformers, Accelerate, and Datasets.
• Strong mathematical foundation and deep knowledge of deep learning algorithms and neural networks, covering both training and inference.
• Proficient in problem-solving, debugging, performance analysis, test design, and documentation.
• Solid understanding of GPU architectures and their applications.
• Excellent Python programming skills and experience with libraries like PyTorch and HuggingFace.
• Familiarity with cloud platforms (preferably AWS), containerization tools like Docker, and deploying AI solutions in cloud environments.
• Strong written and verbal communication skills with the ability to work collaboratively in a dynamic team environment and convey complex ideas effectively.
• Research publications in deep learning are a plus.
• Fluent in English.

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