Software Engineering AI Trainer (Paraguay)

Anyone AI Inc.

Job Overview

Location

Paraguay

Job Type

Part-time

Full Job Description

📋 Description

• Design and implement multi-file coding tasks focused on bug resolution, feature development, refactoring, and migration within production-like software environments.
• Write clear, detailed natural-language specifications that define the scope, requirements, and expected outcomes of each coding task.
• Develop and extend comprehensive unit and integration test suites using frameworks such as pytest, Jest, JUnit, xUnit, or Go testing to validate code correctness and robustness.
• Create reference implementations that serve as accurate, high-quality solutions for the coding tasks you design, ensuring they adhere to production standards.
• Review peer-generated coding tasks and submissions for correctness, clarity, realism, and alignment with specified requirements.
• Identify edge cases, ambiguities, logical inconsistencies, and potential failure modes in both task designs and peer submissions.
• Ensure tight alignment between natural-language specifications, reference code, test suites, and expected outputs to maintain task integrity and evaluative accuracy.
• Navigate and analyze large, complex, multi-file codebases to assess code quality, architecture, and maintainability in peer submissions.
• Perform code reviews that provide structured, actionable feedback to improve the quality and realism of other contributors’ work.
• Participate in production-style software engineering activities including debugging, refactoring, and migration scenarios as part of task creation and evaluation.
• Maintain consistent, professional-level written communication in English throughout all task documentation, feedback, and collaboration.
• Operate independently as a remote, project-based consultant with full control over your schedule and workload.
• Deliver high-quality, production-realistic coding tasks that simulate real-world software engineering challenges for AI training and evaluation purposes.
• Generate complete and correct reference implementations that serve as ground truth for AI model training and performance assessment.
• Produce robust test coverage and validation artifacts that ensure reliability and reproducibility of task outcomes.
• Contribute to an ecosystem where software engineering expertise directly trains and improves large-scale AI models through precise, human-validated data.
• Collaborate asynchronously with a global team of engineers and evaluators while adhering to project deadlines and quality benchmarks.
• Work with modern backend and full-stack technologies in environments mirroring industry-standard development workflows.
• Adapt quickly to evolving task requirements and feedback loops from the AI lab partners to continuously improve task quality.
• Maintain strict separation between your work for Anyone AI and any other vendors or employers, ensuring compliance with all third-party contractual allowances.
• Use your own tools and infrastructure to complete all deliverables, with no provision of equipment or software by the company.

🎯 Requirements

• Advanced professional written proficiency in English
• 3–7 years of professional software engineering experience
• Strong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go
• Backend or full-stack development experience in production systems
• Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing)
• Proven ability to debug and navigate large, multi-file codebases

🏖️ Benefits

• Part-time, project-based compensation paid per-project
• Full flexibility to set your own schedule and workload
• Ability to work remotely from Paraguay
• Opportunity to simultaneously work with other vendors or employers (subject to their policies)

Skills & Technologies

Python

JavaScript

TypeScript

Java

Remote

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Anyone AI Inc.

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About Anyone AI Inc.

Anyone AI provides no-code computer-vision infrastructure that lets companies build, train and deploy image and video models without machine-learning teams. Its cloud platform automates data labeling, model optimization and edge deployment for retail, manufacturing, logistics and healthcare use cases. The company offers pre-trained APIs for object detection, counting and anomaly identification, plus dashboards for continuous monitoring and compliance. Founded in 2021, it targets enterprises seeking rapid AI adoption while avoiding costly specialists and infrastructure setup.

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