Remote AI Trainer & Annotator - Part-Time, Pay Up to $22/hr

Remote AI Trainer & Annotator - Part-Time, Pay Up to $22/hr

Part-Time 22 - 22 £ / hour (est.) Working from home possible
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At a Glance

  • Tasks: Classify data and identify inaccuracies to improve AI through human evaluation.
  • Company: Dynamic AI development firm focused on innovative projects.
  • Benefits: Earn up to $22/hr, flexible hours, and enhance your portfolio.
  • Other info: Perfect for students or freelancers seeking part-time remote work.
  • Why this job: Join a cutting-edge team and make a real impact in AI development.
  • Qualifications: Proficient in Portuguese and advanced in English; higher education preferred.

The predicted salary is between 22 - 22 £ per hour.

An AI development firm is seeking annotators for remote, part-time projects aimed at improving AI through human evaluation.

The role requires individuals who are either currently studying or have completed higher education, especially those proficient in Portuguese and advanced in English.

Responsibilities include classifying data, identifying inaccuracies, and engaging in innovative AI projects.

Compensation can reach up to $22/hour depending on experience and skills, making this an excellent opportunity for students or freelancers looking to enhance their portfolios. #J-18808-Ljbffr

Remote AI Trainer & Annotator - Part-Time, Pay Up to $22/hr employer: Toloka Annotators

Join a forward-thinking AI development firm that values innovation and creativity, offering flexible remote work opportunities tailored for students and freelancers. With competitive pay of up to $22/hour, our supportive work culture encourages personal growth and skill enhancement while contributing to cutting-edge AI projects. Experience the unique advantage of working in a dynamic environment that fosters collaboration and professional development.

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Contact Details:

Toloka Annotators Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Remote AI Trainer & Annotator - Part-Time, Pay Up to $22/hr

Get Involved in Data Challenges

Participate in data challenges like Kaggle competitions or DrivenData to showcase your skills and network with other data enthusiasts. Not only will you build your portfolio, but you can also catch the eye of potential employers like Toloka Annotators.

Connect with Local Data Communities

Join local data science meetups or online communities like Data Science Society to engage with professionals in the field. These platforms are great for networking, discovering job opportunities, and keeping your fingers on the pulse of industry trends.

Leverage Your University’s Resources

If you're still in university, make full use of your career services. They might have part-time roles tailored for students like you, and often have direct connections with companies looking to hire talented interns in data science roles.

Apply Directly Through Our Website

Don’t forget to check out our jobs at Toloka Annotators and apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate individuals like us who are eager to make an impact in the data science world.

We think you need these skills to ace Remote AI Trainer & Annotator - Part-Time, Pay Up to $22/hr

Data Classification
Attention to Detail
Language Proficiency in Portuguese
Advanced English Skills
Critical Thinking
Problem Identification
Innovative Thinking

Some tips for your application 🫡

Show Your Data Skills:In your CV, make sure to highlight your proficiency with key data analysis tools and programming languages like Python, R, or SQL. We want to see that you've got hands-on experience with data manipulation and visualisation, so if you've worked on any relevant projects or coursework, include those details to really showcase your skills!

Tailor Your Projects Towards Data Science:When it comes to your portfolio, focus on showcasing projects that highlight your data-science abilities. Include analyses, dashboards, or any predictive models you've built. If you've contributed to Kaggle competitions or have a GitHub repository with data projects, make sure to link those—these demonstrate your practical experience and problem-solving abilities.

Express Your Motivation in the Cover Letter:Since this is a part-time role, we want to know why you're particularly interested in juggling this with your other commitments. Use your cover letter to express your passion for data science and how this role at Toloka Annotators aligns with your career aspirations. Show us you're excited about learning and growing with us!

Keep It Concise Yet Informative:Part-time positions often receive many applications, so keep your documents clear and to the point! Aim for a concise CV detailing your relevant experiences without unnecessary fluff. Be sure to include your availability in your cover letter as well—that helps us in the decision-making process!

How to prepare for a job interview at Toloka Annotators

Brush Up on Your Stats!

Given you're eyeing a part-time role in data science, make sure you’re on top of your statistical methods and data analysis techniques. Expect questions around regression, hypothesis testing, and maybe even some statistical programming languages like R or Python during the interview with Toloka Annotators.

Show Off Your Projects!

It's crucial to have a portfolio that showcases your data science projects. Highlight your part-time work with specific data sets, models you've built, or analyses you've conducted. Having tangible examples will demonstrate your hands-on experience and problem-solving skills to Toloka Annotators.

Familiarise Yourself with Tools of the Trade

Make sure you’re well-versed in data science tools like Jupyter Notebook, Tableau, or SQL. You might get technical questions or even a practical test at Toloka Annotators, so having a comfort level with these tools will definitely be an advantage.

Be Ready to Discuss Real-World Applications

Since this is a part-time role, employers at Toloka Annotators will likely appreciate your understanding of how data science can address actual business problems. Be prepared to discuss any relevant case studies or how you would approach specific challenges in real scenarios.