Machine Learning Engineer

hace 2 semanas

San Sebastián, Guipúzcoa, España beBee Careers A tiempo completo
Machine Learning Engineer - AI Research

We are seeking a highly skilled Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will be responsible for developing and refining state-of-the-art deep learning models with a focus on NLP and LLMs.

This is a fantastic opportunity for experienced engineers who want to work on cutting-edge AI technology and collaborate with global experts to develop innovative solutions.

The ideal candidate will have a strong background in machine learning, computer science, or a related field, with hands-on experience in deep learning and NLP. They will also have excellent programming skills in Python, with experience using PyTorch, Hugging Face, and other ML libraries.

Responsibilities:

- Develop and refine state-of-the-art deep learning models with a focus on NLP and LLMs.
- Work on AI model compression using advanced techniques such as Tensor Networks to enhance efficiency and portability.
- Optimize, test, and deploy AI solutions on cloud environments (preferably AWS) using containerization technologies like Docker.
- Implement and optimize ML model pipelines, ensuring high performance and scalability.
- Collaborate with global AI and quantum computing experts to develop solutions addressing real-world industry challenges.
- Apply GPU acceleration techniques to improve AI model performance and efficiency.
- Stay informed on cutting-edge AI/ML advancements, contributing to research and development efforts.

Requirements:

- Master's or Ph.D. in Artificial Intelligence, Computer Science, Machine Learning, Data Science, or a related field.
- 4+ years of hands-on experience in deep learning and machine learning models within an industry setting.
- Strong expertise in NLP and LLMs such as LLaMA, Claude, Mistral, YOLO, or Falcon.
- Excellent programming skills in Python, with experience using PyTorch, Hugging Face, and other ML libraries.
- Deep understanding of GPU architectures and performance optimization techniques.
- Proven ability to deploy deep learning models in cloud environments (AWS preferred).
- Experience with containerization tools (Docker) and MLOps best practices.
- Excellent problem-solving and debugging skills, with strong written and verbal communication abilities.

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