Data Engineer - AI Trainer
DataAnnotation · North Carolina, United States
- Hybrid
- Full-time
- $100,000 / year
- North Carolina, United States
Job highlights
- Remote Data Engineer role for AI system development.
- Design and solve coding problems for AI training.
- Evaluate AI-generated code and provide feedback.
- Flexible schedule with competitive hourly pay.
- Contribute to shaping future AI technologies.
About the role
Data Engineer AI Trainer
Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule.
We are looking for proficient programmers to help advance AI development. As a member of DataAnnotation’s coding team, you’ll be part of a growing community of over 100,000 professionals — including front-end, back-end, full-stack, machine learning, and other engineers — who are driving real-world impact in AI development.
Our platform offers an engaging blend of flexibility and challenge: you’ll work closely with state-of the art AI models to take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and visualization. Your work directly contributes to refining intelligent systems that learn, adapt, and evolve. Some team members fit this work alongside a full-time role, while others treat it as their primary focus, choosing projects and schedules that align with their availability and goals.
To get started
Once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass that assessment, you’ll receive an email confirmation, and paid work will become available to you through our platform.
Benefits
- Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
- Flexible schedule: choose which projects you take on and when you work.
- Competitive pay: projects are paid hourly, starting at $50-$100+/hr. Opportunities for higher-paying projects are available with strong performance.
- Impact: help shape the future of AI technologies.
Responsibilities
- Design and solve diverse coding problems used to train AI systems with an emphasis on Android development.
- Write clear, high-quality code snippets and detailed explanations.
- Evaluate AI-generated code for accuracy, performance, and clarity.
- Provide feedback that directly shapes the next generation of AI models.
Qualifications
- Fluency in English (native or bilingual level).
- Preferred experience in Kotlin.
- Proficiency in at least one of other the following programming languages or frameworks: JavaScript, TypeScript, Python, C, C#, C++, React, Go, Java, or Swift.
- Excellent writing and grammar skills.
- A bachelor’s degree (completed or in progress).
- Previous experience as a Software Developer, Coder, Software Engineer, or Programmer is preferred.
Note
Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. Those located outside of these countries will not see work or assessments available on our site at this time.
Key skills/competency
- Data Engineering
- AI Training
- Programming
- Android Development
- Kotlin
- JavaScript
- Python
- Software Development
- Code Evaluation
- Problem Solving
Skills & topics
- Data Engineer
- AI Trainer
- Programmer
- Kotlin
- Android Development
- JavaScript
- Python
- Software Engineer
- Remote Work
- AI Development
How to get hired
- Take the assessment: Complete the short online assessment to demonstrate your coding skills.
- Prepare your resume: Highlight your programming experience, especially in Kotlin, and any relevant AI contributions.
- Showcase language proficiency: Emphasize your fluency in English and any listed programming languages.
- Understand the process: Be aware that work becomes available after passing the assessment and confirmation.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the application process for a Data Engineer AI Trainer at DataAnnotation?
- The application process for a Data Engineer AI Trainer at DataAnnotation involves signing up for an account and completing a short online assessment. Passing this assessment serves as the interview, after which you will receive an email confirmation and access to paid work on the platform.
- What programming languages are most important for the Data Engineer AI Trainer role at DataAnnotation?
- While fluency in English and a bachelor's degree are required, preferred experience in Kotlin is highly valued for the Data Engineer AI Trainer role. Proficiency in other languages like JavaScript, TypeScript, Python, C, C#, C++, React, Go, Java, or Swift is also beneficial.
- Can I work as a Data Engineer AI Trainer at DataAnnotation while holding a full-time job?
- Yes, the Data Annotation platform offers a flexible schedule. Many team members fit this work alongside a full-time role, choosing projects and schedules that align with their availability and goals. Some also treat it as their primary focus.
- What is the expected pay for a Data Engineer AI Trainer at DataAnnotation?
- Data Annotation offers competitive hourly pay for Data Engineer AI Trainer roles, starting at $50-$100+ per hour. Opportunities for higher-paying projects are available for those who demonstrate strong performance.
- What are the geographic requirements for the Data Engineer AI Trainer position at DataAnnotation?
- The Data Engineer AI Trainer position is fully remote and available only to individuals located in the US, Canada, UK, Ireland, Australia, and New Zealand. If you are outside of these countries, you will not see work or assessments available on their site.
- What kind of tasks can I expect as a Data Engineer AI Trainer at DataAnnotation?
- As a Data Engineer AI Trainer, you will design and solve coding problems to train AI systems, with an emphasis on Android development. You will also write code snippets, detailed explanations, evaluate AI-generated code, and provide feedback to refine AI models.