LLM Fine-Tuning Research Intern

Mistral; Paris; In loco; EUR 17.000 - 23.000; Tempo pieno

Vantaggi offerti da questo lavoro

Healthcare coverage

Relocation support

Meal and transportation allowances

Location-specific perks

Descrizione del lavoro

Mistral is seeking a motivated intern to join their pre-training and fine-tuning LLM team in Paris. You will work on state-of-the-art generative models under supervision, contributing to model design, implementation, and research while gaining exposure to a full ML lifecycle.

The internship is 6 months, suitable for Master or PhD candidates, with opportunities to explore MLOps, production-grade code, and collaboration across global teams. Based in Paris with potential for other offices.

Competenze

• Master's or PhD in a STEM field from a top-tier school.
• Strong foundation in ML/NLP and model fine-tuning concepts.
• Experience with Python ML libraries and NLP pipelines.
• Familiarity with MLOps and production-ready software.

Mansioni

• Work with fine-tuning team on state-of-the-art generative models.
• Run autonomous work streams under senior scientists guidance.
• Collaborate with cross-functional teams to integrate LLMs into applications.
• Design and implement ML models and algorithms relevant to LLMs.
• Perform data analysis and visualization to support research.
• Document findings for technical reports/publications.
• Contribute to the development and optimization of LLM systems.
• Participate in team meetings to share ideas and insights.

Conoscenze

Python programming

NLP fundamentals

ML algorithms

Research skills

Data analysis

Communication

Formazione

Master's or PhD in STEM

Strumenti

TensorFlow

PyTorch

Git

Linux shell

Descrizione del lavoro

Mistral is seeking a motivated intern to join their pre-training and fine-tuning LLM team in Paris. You will work on state-of-the-art generative models under supervision, contributing to model design, implementation, and research while gaining exposure to a full ML lifecycle.

The internship is 6 months, suitable for Master or PhD candidates, with opportunities to explore MLOps, production-grade code, and collaboration across global teams. Based in Paris with potential for other offices.