Applied scientist intern
- Perform comprehensive literature review on LLMs and their applications in recommendation systems.
- Gather and preprocess data from various sources, ensuring its adequacy for recommendation tasks.
- Investigate the effectiveness of LLMs in recommendation scenarios where no direct training data is available.
- Implement evaluation pipelines and conduct thorough experiments to assess the recommendation capabilities of LLMs.
- Implement/refine finetuning and pretraining techniques for LLMs, specifically focusing on recommendation tasks.
- Collaborate closely with the team to analyze and interpret experimental results.
- Document your findings and contribute to prototyping LLMs-based recommendation solutions.
- Currently enrolled in a computer science Master 2 program (or equivalent) specialized in machine learning.
- Strong programming skills, preferably in Python, and experience with deep learning frameworks such as PyTorch.
- Strong machine learning background and familiarity with recommendation systems, natural language processing (NLP).
- Solid understanding of transformer architectures, especially in the context of LLMs.
- Proficiency in leveraging existing datasets and data preprocessing techniques for machine learning tasks.
- Excellent analytical and problem-solving skills, as well as attention to detail.
- Full proficiency in English and the ability to work independently and collaboratively as part of a team.
- Compensation ranges : 1 100 to 1 320 ₠
- Lunch vouchers
- Office in Sentier neighbourhood
- Being part of multicultural teams with more than 20 nationalities
- Gain practical experience in cutting-edge research and technologies.
- Work in a collaborative and supportive environment with experienced scientists and engineers.
- Access to relevant resources, datasets, and computational resources.
- Potential authorship on research publications and technical reports.
English (Overall - 3 - Advanced)
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