Applied Scientist (Internship)
Standard baseline compensation
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Paris
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Job Description & Specifications
Official role breakdown, eligibility standards, and core responsibilities
Applied Scientist (Internship) at Mistral.ai
📍 Paris
What You Will Do
- Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs.
- Generate and curate data for pre-training and post-training, working on evaluations and making sure the model's performance beats expectations.
- Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deployment.
- Collaborate with cross-functional teams to tackle complex use cases using agents and retrieval pipelines.
- Manage research projects and communications with client research teams.
What We're Looking For
- Fluent in English with excellent communication skills — at ease explaining complex technical concepts to both technical and non-technical audiences.
- Expert with PyTorch or JAX.
- Not afraid of contributing to a big codebase; finds their way around independently with little guidance.
- Writes clean, readable, high-performance, fault-tolerant Python code.
- Doesn’t need roadmaps: moves independently and navigates uncertainty with confidence.
- Low-ego, collaborative and eager to learn.
- Track record of success through personal projects, professional projects or academia.
Nice to have
Location & work authorization: This internship is available only in France or the UK. Please apply only if you have the required work authorization to complete the internship in the relevant country for its full duration.
- Pursuing a PhD / Master in a relevant field (Mathematics, Physics, Machine Learning) — exceptional candidates from other backgrounds welcome.
- Preferred duration: at least 6 months. Priority to candidates about to finalise their studies.
- Research experience in agents, multimodal models, world models, robotics, diffusion models, cybersecurity, 3D understanding/generation, or time-series analysis.
- Contributions to a large open-source or industry codebase.
- Publications in top academic journals or conferences.
- Enjoys improving existing code: typing, tests, CI pipelines.
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