At a Glance
- Tasks: Design and operate cutting-edge data infrastructure for AI training and fine-tuning.
- Company: Join Mistral, a leader in AI compute platforms with a focus on innovation.
- Benefits: Attractive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with exciting challenges and career advancement potential.
- Why this job: Be at the forefront of AI technology and make a significant impact in the field.
- Qualifications: Experience in data infrastructure and strong problem-solving skills required.
The predicted salary is between 70000 - 90000 £ per year.
Mistral is seeking a Data Infrastructure professional to design and operate the next generation of our data infra for training and fine‑tuning at scale.
You will help build massive compute fleets and storage systems, ensuring secure and governed data access for MLOps and research across hybrid environments.
You will own end‑to‑end migration from legacy orchestrators to production‑grade pipelines and participate in on‑call rotations for critical training jobs.
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Senior Data Infrastructure Engineer, AI Compute Platform in London employer: mistral
Mistral is an exceptional employer located in the vibrant Greater London area, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from competitive salaries, equity options, comprehensive health insurance, and visa sponsorship, alongside ample opportunities for professional growth within the rapidly evolving field of AI. Joining Mistral means being part of a forward-thinking team dedicated to making a meaningful impact through strategic partnerships with leading publishers and academic institutions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Infrastructure Engineer, AI Compute Platform in London
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We think you need these skills to ace Senior Data Infrastructure Engineer, AI Compute Platform in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
