Automated QA Engineer - AI Trainer

Automated QA Engineer - AI Trainer

DataAnnotation

Springfield, IL • On-site, Remote

$60/hr

Full-time

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Job description

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, up to $60 USD/hour. 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 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. #J-18808-Ljbffr




Frequently asked questions

Q: What skills or qualities help someone succeed as a Software Quality Engineer?

A: To succeed as a Software Quality Engineer, key technical skills include proficiency in programming languages such as Python or Java, experience with testing frameworks like JUnit or PyUnit, and knowledge of agile methodologies like Scrum or Kanban. Soft skills like effective communication, problem-solving, and analytical thinking are also crucial, as they enable Quality Engineers to collaborate with cross-functional teams, identify and prioritize defects, and develop efficient testing strategies. By combining these technical and soft skills, a Software Quality Engineer can drive quality improvement, reduce defects, and contribute to the overall success of software development projects.

Q: What is the career path for a Software Quality Engineer?

A: A Software Quality Engineer's typical career progression involves starting as a Quality Assurance (QA) Engineer, then advancing to roles such as Test Automation Engineer, Senior QA Engineer, and eventually, a Quality Engineering Manager or Technical Lead. Key opportunities for skill development include learning programming languages like Python or Java, mastering test automation frameworks, and gaining expertise in Agile methodologies and DevOps practices. Long-term career prospects may lead to roles in technical leadership, product management, or even transitioning into related fields like IT project management or technical consulting.



DataAnnotation job posting for a Automated QA Engineer - AI Trainer in Springfield, IL with a salary of $60 Hourly with a map of Springfield location.