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- Tasks: Review data annotations for AI models and enhance internal tools.
- Company: Join Mistral AI, a leading tech company in Greater London.
- Benefits: Enjoy a competitive salary, pension plan, transport reimbursement, and gym membership.
- Other info: Hybrid role offering a dynamic work environment and growth opportunities.
- Why this job: Be part of an innovative team shaping the future of AI technology.
- Qualifications: Degree in computer science or similar, with software engineering experience.
The predicted salary is between 40000 - 50000 £ per year.
Mistral AI in Greater London is seeking a Data Quality Specialist to join their Human Data Annotation team. The ideal candidate will have strong analytical skills, a degree in computer science or similar, and hands-on experience in software engineering. This hybrid role involves reviewing data annotations for AI models and improving internal tooling.
Benefits include:
- Competitive salary
- Pension plan
- Transportation reimbursement
- Gym membership allowances
AI Data Quality Specialist & Annotation Tools employer: Mistral AI
Contact Detail:
Mistral AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Data Quality Specialist & Annotation Tools
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and data quality space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your analytical projects or any software engineering work. This gives you a chance to shine beyond the usual application.
✨Tip Number 3
Prepare for those interviews! Research Mistral AI, understand their products, and think about how your experience aligns with their needs. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace AI Data Quality Specialist & Annotation Tools
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your analytical skills and any relevant experience in software engineering. We want to see how your background aligns with the role of an AI Data Quality Specialist.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data quality and AI. Share specific examples of your hands-on experience that demonstrate your fit for the Human Data Annotation team.
Showcase Your Technical Skills: Don’t forget to mention any tools or technologies you’ve worked with that are relevant to data annotation and quality assurance. We love seeing candidates who can bring their technical expertise to the table!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity at Mistral AI!
How to prepare for a job interview at Mistral AI
✨Know Your Data Inside Out
Make sure you brush up on your understanding of data quality and annotation processes. Familiarise yourself with common pitfalls in data annotation and be ready to discuss how you would address them. This will show that you’re not just knowledgeable but also proactive about improving data quality.
✨Show Off Your Analytical Skills
Prepare to demonstrate your analytical skills during the interview. Bring examples from your past experiences where you successfully identified issues in data or improved processes. Use specific metrics or outcomes to highlight your contributions, as this will resonate well with the hiring team.
✨Get Comfortable with Tools
Since the role involves improving internal tooling, it’s crucial to be familiar with the tools used in data annotation and quality assurance. If you’ve worked with any relevant software or programming languages, be ready to discuss your experience and how you can leverage these tools to enhance their processes.
✨Ask Insightful Questions
Prepare a few thoughtful questions about Mistral AI's current projects or challenges they face in data quality. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you. Plus, it gives you a chance to engage in a meaningful conversation with your interviewers.