Anyone AI Inc. logo

Software Engineering AI Trainer (Mexico)

Job Overview

Location

Mexico - Fully Remote

Job Type

Contract

Category

Software Engineering

Date Posted

April 22, 2026

Full Job Description

📋 Description

  • Software Engineering AI Trainer (Mexico) – A remote, part-time project-based role where skilled software engineers design and evaluate realistic coding tasks for a leading AI lab, contributing to the advancement of AI training data quality and reliability.
  • Day-to-day responsibilities include designing multi-file coding tasks (bug fixes, feature development, refactoring, testing), writing clear natural-language specifications and reference implementations, developing unit and integration test suites, reviewing peer submissions for correctness and realism, identifying edge cases and ambiguities, and ensuring alignment between specifications, code, and expected outputs.
  • Anyone AI Inc. is a remote-first company collaborating with top AI labs to build high-fidelity training data for AI systems; this role sits at the intersection of software engineering and AI development, offering exposure to cutting-edge AI evaluation methodologies.
  • Contributors will deepen their expertise in software design, test-driven development, code review, and AI alignment practices while building a portfolio of production-realistic coding scenarios used to train and evaluate state-of-the-art AI models.

Skills & Technologies

Python
JavaScript
TypeScript
Java
Go
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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