Requirements: English
Company: European Tech Recruit
Region: San Sebastin , Basque Country
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 Masters 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 and Spanish is a must.
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