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Full-Stack Developer - AI Trainer (Peru)

Job Overview

Location

Peru - Fully Remote

Job Type

Contract

Category

Software Engineering

Date Posted

June 13, 2026

Full Job Description

đź“‹ Description

  • • Design and implement multi-file coding tasks focused on bug resolution, feature development, refactoring, and test generation for AI training datasets.
  • • Write clear, precise natural-language specifications and reference implementations that accurately reflect real-world software engineering scenarios.
  • • Develop and extend unit and integration test suites using frameworks such as pytest, Jest, JUnit, xUnit, or Go testing to validate code behavior and edge cases.
  • • Review peer-generated coding tasks for correctness, clarity, realism, and alignment with specifications and expected outputs.
  • • Identify ambiguities, edge cases, potential failure modes, and inconsistencies between code, documentation, and intended functionality.
  • • Ensure strict alignment between task specifications, reference implementations, and test coverage to produce production-realistic training data for AI models.
  • • Work within large, complex codebases to debug issues, navigate dependencies, and perform refactoring or migration tasks as required.
  • • Contribute to the creation of high-quality, scalable coding challenges used to evaluate and train AI systems in software engineering tasks.
  • • Operate independently with full control over schedule and workflow, delivering project-based outputs on agreed timelines.
  • • Maintain professional written proficiency in English to produce clear, grammatically accurate technical documentation and feedback.
  • • Collaborate asynchronously with a global team of AI trainers and engineers to refine task quality and consistency across the platform.
  • • Use own tools and infrastructure; no company-provided equipment or software is provided.
  • • Accept payment on a per-project basis, with rates estimated based on anticipated completion time and complexity.
  • • May simultaneously engage with other vendors or employers, provided such arrangements do not conflict with project obligations or confidentiality requirements.
  • • Participate in iterative feedback loops to improve task design, test robustness, and evaluation criteria based on AI model performance data.
  • • Contribute structured, actionable peer review feedback that highlights strengths, weaknesses, and opportunities for improvement in submitted solutions.
  • • Deliver complete and correct reference implementations that serve as gold-standard examples for AI training and evaluation.
  • • Generate validation artifacts including test results, logs, and documentation to support auditability and reproducibility of coding tasks.

🎯 Requirements

  • • Advanced professional written proficiency in English
  • • 3–7 years of professional software engineering experience
  • • Strong proficiency in Python and JavaScript/TypeScript
  • • 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

  • • Flexible, project-based work with full schedule control
  • • Payment on a per-project basis with rates tied to task complexity
  • • Opportunity to work remotely from Peru with no location restrictions
  • • Ability to simultaneously work with other vendors or employers (subject to their policies)

Skills & Technologies

Python
JavaScript
TypeScript
Java
Go
Full Stack
Remote

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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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