At a Glance
- Tasks: Evaluate and label data like text, audio, and video for machine learning projects.
- Company: Join Yellowcat, a dynamic company at the forefront of AI research.
- Benefits: Earn £140 daily plus holiday allowance, paid weekly.
- Other info: Onsite role in central London for 6 months with great networking opportunities.
- Why this job: Make an impact in AI while honing your analytical and writing skills.
- Qualifications: Fluency in French and English with strong business writing skills.
The predicted salary is between 36400 - 36400 € per year.
Yellowcat is seeking a temporary Machine Learning Assistant for a 6-month project in central London. The role involves evaluating data such as text, audio, and video to deliver high-quality labelled data.
Ideal candidates will be fluent in French and English and possess strong business writing and analytical skills. The position requires working onsite in central London, with a daily rate of £140 plus holiday allowance, paid weekly via PAYE.
French AI Data Labeling & Researcher (London, 6 months) employer: Yellowcat
At Yellowcat, we pride ourselves on fostering a dynamic and inclusive work culture that values innovation and collaboration. As a temporary Machine Learning Assistant in the heart of London, you'll enjoy competitive pay, flexible working arrangements, and the opportunity to enhance your skills in a cutting-edge field. Join us for a rewarding experience where your contributions directly impact the quality of AI data solutions.
StudySmarter Expert Advice🤫
We think this is how you could land French AI Data Labeling & Researcher (London, 6 months)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your skills. We recommend doing mock interviews with friends or using online resources to boost your confidence.
✨Tip Number 3
Showcase your passion for AI and data labeling during interviews. Share relevant projects or experiences that highlight your analytical skills and fluency in French and English.
✨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 the initiative!
We think you need these skills to ace French AI Data Labeling & Researcher (London, 6 months)
Some tips for your application 🫡
Show Off Your Language Skills:Since the role requires fluency in both French and English, make sure to highlight your language skills right at the start. We want to see how you can communicate effectively in both languages!
Tailor Your Writing Style:Use a professional yet approachable tone in your application. We appreciate strong business writing, so keep it clear and concise while showcasing your personality. Let us know why you're the perfect fit for this role!
Highlight Relevant Experience:If you've worked with data before or have experience in machine learning, be sure to mention it! We love seeing how your past experiences align with what we’re looking for in this position.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you don’t miss out on any important updates about your application!
How to prepare for a job interview at Yellowcat
✨Brush Up on Your French and English
Since the role requires fluency in both languages, make sure to practice your language skills before the interview. You might be asked to demonstrate your proficiency, so consider preparing a few examples of business writing or analytical discussions in both French and English.
✨Know Your Data Evaluation Techniques
Familiarise yourself with common data evaluation methods, especially for text, audio, and video. Be ready to discuss how you would approach labelling data and what tools or techniques you’ve used in the past. This shows that you’re not just a language expert but also understand the technical side of the job.
✨Prepare for Scenario-Based Questions
Expect questions that put you in real-life scenarios related to data labelling and research. Think about how you would handle specific challenges, such as dealing with ambiguous data or ensuring quality control. Practising these scenarios can help you articulate your thought process clearly during the interview.
✨Show Enthusiasm for the Project
Let your passion for machine learning and data research shine through. Research Yellowcat and their projects, and be prepared to discuss why you’re excited about this particular role. A genuine interest can set you apart from other candidates and show that you’re a great fit for the team.
