Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Categorise, annotate, transcribe, and create content for exciting linguistic projects.
- Company: Join Sigma AI, a leading global tech company in the AI space.
- Benefits: Collaborative environment with opportunities to grow your skills.
- Other info: Perfect for those looking to kickstart their career in tech!
- Why this job: Make an impact in AI while using your language skills every day.
- Qualifications: Native or bilingual Mongolian speaker fluent in English; basic computer skills required.
The predicted salary is between 30000 - 40000 £ per year.
Sigma AI is looking for a qualified candidate to join their linguistic projects in Greater London, UK. The role requires a native or bilingual Mongolian speaker who is fluent in English.
Responsibilities include:
- Categorization
- Annotation
- Transcription
- Content creation
Candidates should possess basic computer skills, and experience in data annotation is a plus. This opportunity involves working within a leading global technology company specialized in AI, offering a vibrant and collaborative environment.
Mongolian Language Data Annotations — London employer: Sigma AI
Contact Detail:
Sigma AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Mongolian Language Data Annotations — London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and linguistic fields on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Prepare for interviews by brushing up on your data annotation skills. Practice explaining your experience with categorization and transcription clearly, as this will show you're ready to hit the ground running in the role.
✨Tip Number 3
Don’t just apply anywhere—focus on companies that excite you! Use our website to find roles that match your skills and interests, and tailor your approach to each one. A personal touch goes a long way!
✨Tip Number 4
Follow up after interviews! A quick thank-you email can keep you top of mind for the hiring team. It shows your enthusiasm for the role and gives you another chance to highlight why you’re the perfect fit.
We think you need these skills to ace Mongolian Language Data Annotations — London
Some tips for your application 🫡
Show Off Your Language Skills: Make sure to highlight your fluency in both Mongolian and English. We want to see how you can navigate between the two languages, so don’t hold back on showcasing your linguistic prowess!
Tailor Your Application: Take a moment to customise your application for this role. Mention any relevant experience in data annotation or similar tasks. We love seeing how your background aligns with what we’re looking for!
Keep It Clear and Concise: When writing your application, clarity is key! Use straightforward language and get to the point. We appreciate well-structured applications that are easy to read.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity.
How to prepare for a job interview at Sigma AI
✨Brush Up on Your Language Skills
Make sure you're comfortable with both Mongolian and English. Practise speaking and writing in both languages, as you might be asked to demonstrate your fluency during the interview.
✨Familiarise Yourself with Data Annotation
Since experience in data annotation is a plus, it’s a good idea to understand the basics of the process. Look up common tools and techniques used in data annotation to show your enthusiasm and readiness to learn.
✨Showcase Your Computer Skills
Basic computer skills are essential for this role. Be prepared to discuss your proficiency with software and any relevant tools you’ve used in the past. If you have experience with specific annotation tools, mention them!
✨Emphasise Teamwork and Collaboration
Sigma AI values a vibrant and collaborative environment. Think of examples from your past experiences where you worked well in a team, and be ready to share how you can contribute positively to their projects.