Applied Scientist Internship
Mistral AI
entry-level
Location
London, United Kingdom
Work Type
Onsite
Seniority
entry-level
Posted
September 2, 2026
Total Compensation
€81,250
Yearly Savings (Comfortable)
€-6,668
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Job Description
Who you are
- 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
- 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
What the job involves
- Mistral AI is seeking Applied Scientist Interns and Research Engineer Interns to drive innovative research and collaborate with clients on complex research projects
- You will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas you will apply these models across a diverse set of use cases and domains. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions that turn the needle
- 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
Benefits
- Competitive bonus structure
- Equity
- Opportunities for professional growth and development
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