Applied Scientist, Multimodal AI (EMEA)

Applied Scientist, Multimodal AI (EMEA)

Full-Time 75645 - 92455 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Drive innovative research and develop state-of-the-art AI models across text, image, and speech.
  • Company: Mistral AI, a leader in multimodal AI solutions with a collaborative culture.
  • Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
  • Other info: Join a dynamic team focused on delivering high-impact AI solutions.
  • Why this job: Make a real impact by solving complex problems with cutting-edge AI technology.
  • Qualifications: Experience in AI research and strong collaboration skills are essential.

The predicted salary is between 75645 - 92455 £ per year.

Mistral AI is seeking Applied Scientists and Research Engineers to drive innovative research and collaborate with clients on complex projects across AI modalities.

You will develop SOTA models across text, image, and speech, create novel methods, and work with cross-functional teams to deliver high-impact AI solutions for real-world use cases.

Our team values collaboration and impact.

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Applied Scientist, Multimodal AI (EMEA) employer: Mistral AI

Mistral AI is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a WAN & Edge Network Automation Engineer to thrive. With a strong emphasis on employee growth, you will have access to continuous learning opportunities and cutting-edge projects that challenge your skills. Located in a vibrant tech hub, the company offers a dynamic work environment where creativity and teamwork are highly valued, ensuring that every team member contributes to meaningful advancements in network automation.

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Contact Details:

Mistral AI Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Applied Scientist, Multimodal AI (EMEA)

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Mistral AI!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Applied Scientist, Multimodal AI (EMEA) at Mistral AI.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Mistral AI.

✨Apply Directly through Our Website

When you find a suitable opening like Applied Scientist, Multimodal AI (EMEA) at Mistral AI, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Applied Scientist, Multimodal AI (EMEA)

Applied Science
Research Skills
AI Modalities
Model Development
Text Processing
Image Processing
Speech Processing

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Mistral AI, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Mistral AI. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Mistral AI

✨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!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Mistral AI!

✨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.