Job Overview
Location
Uruguay
Job Type
Contract
Category
Software Engineering
Date Posted
June 4, 2026
Full Job Description
📋 Description
- • Design and implement multi-file coding tasks focused on bug resolution, feature implementation, refactoring, and migration in production-like environments.
- • Write clear, precise natural-language specifications that define coding challenges and expected outcomes for AI training purposes.
- • Develop and extend comprehensive unit and integration test suites using frameworks such as pytest, Jest, JUnit, xUnit, or Go testing to validate code correctness.
- • Create realistic, production-grade reference implementations in Python, JavaScript/TypeScript, and optionally Java, C#, or Go.
- • Review peer-generated coding tasks for correctness, clarity, realism, and alignment with specifications and expected outputs.
- • Identify edge cases, ambiguities, logical flaws, and potential failure modes in both task designs and submitted solutions.
- • Ensure strict consistency between task specifications, reference code, and test artifacts to maintain high-fidelity AI training data.
- • Contribute to the evaluation of software engineering scenarios that simulate real-world development workflows and codebase navigation.
- • Work independently on a project-based, part-time basis with full control over schedule and workload pacing.
- • Operate as a remote consultant using personal tools and infrastructure, with no requirement for fixed hours or team collaboration.
- • Deliver structured, actionable feedback on peer submissions, highlighting strengths, weaknesses, and opportunities for improvement.
- • Maintain high standards of code quality, documentation clarity, and testing rigor across all delivered artifacts.
- • Participate in iterative task refinement cycles based on feedback from the AI lab team to improve task realism and educational value.
- • Adhere to professional coding standards and best practices in all deliverables, ensuring outputs are indistinguishable from real-world engineering work.
- • Manage multiple concurrent projects with varying complexity and deadlines while maintaining accuracy and timeliness.
- • Collaborate asynchronously with a global team of engineers and evaluators to uphold consistency in task quality and evaluation criteria.
- • Contribute to the continuous improvement of AI training datasets by identifying gaps in task diversity, difficulty, and realism.
- • Retain the right to provide services to other vendors or employers, provided such activities do not conflict with project obligations or confidentiality.
🎯 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
- • Project-based compensation paid per task, with rates estimated based on anticipated completion time
- • Full flexibility to set own schedule and work pace
- • Ability to work remotely with no location restrictions
- • Opportunity to work alongside a leading AI lab on cutting-edge training data development
- • Permission to simultaneously engage with other vendors or employers (subject to their policies)
- • Use of personal tools and infrastructure with no required equipment investment
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
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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