GenAI Deployment Engineer Intern

Mistral.ai

Paris

Sur place

EUR 11 000 - 17 000

Plein temps

Il y a 4 jours
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Avantages offerts par ce poste

Healthcare cover
Parental leave
Relocation support
Wellness program
Meal allowance

Résumé du poste

Mistral.ai is seeking an Applied Engineering Intern in Paris to work with the Applied AI Engineering team, helping customers adopt our GenAI products and tackle technical challenges. The internship lasts 3 to 6 months, with CIFRE opportunities as a continuation after the internship.

You will collaborate with researchers, AI engineers, and product engineers on customer projects, contributing to deployment of GenAI applications and helping improve product and model capabilities based on feedback.

Qualifications

  • Pursuing a degree in AI, data science, or related field from a top-tier institution.
  • Strong Python programming skills.
  • Familiar with ML algorithms and NLP techniques.
  • Basic understanding of MLOps and deploying ML use cases.
  • Good communication skills to explain technical concepts to varied audiences.

Responsabilités

  • Contribute to deployment of state-of-the-art GenAI applications for customers.
  • Collaborate with researchers, AI engineers, and product engineers on customer projects.
  • Work with product and science teams to improve product/model capabilities based on feedback.

Connaissances

Python
ML concepts
NLP
Communication

Formation

AI/Data science degree (tier 1 engineering school/university)

Outils

PyTorch
Git
Linux shell
HPC environments

Description du poste

Mistral.ai is seeking an Applied Engineering Intern in Paris to work with the Applied AI Engineering team, helping customers adopt our GenAI products and tackle technical challenges. The internship lasts 3 to 6 months, with CIFRE opportunities as a continuation after the internship.

You will collaborate with researchers, AI engineers, and product engineers on customer projects, contributing to deployment of GenAI applications and helping improve product and model capabilities based on feedback.

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