Software Engineering AI Trainer (Ecuador)

Anyone AI Inc.

Job Overview

Location

Ecuador - Fully Remote

Job Type

Part-time

Full Job Description

📋 Description

• Are you a seasoned software engineer with a passion for elevating the quality and realism of AI training data? Anyone AI Inc. is seeking talented individuals to join our team as Project Consultants, contributing to the cutting edge of artificial intelligence development by creating and evaluating sophisticated software engineering tasks. This unique opportunity allows you to leverage your extensive experience in a flexible, remote, project-based role, shaping the future of AI-powered software development.
• In this pivotal role, you will be instrumental in designing and implementing a diverse range of multi-file coding tasks. Your day-to-day responsibilities will encompass the full spectrum of software development challenges, including identifying and resolving complex bugs, implementing new features that push the boundaries of existing systems, undertaking intricate refactoring and migration projects to optimize codebases, and meticulously generating comprehensive test suites. You will be tasked with crafting realistic scenarios that accurately reflect the complexities of production environments, ensuring that our AI models are trained on the most relevant and challenging data possible.
• A significant part of your contribution will involve writing clear, concise, and unambiguous natural-language specifications that precisely define the requirements for each coding task. Alongside these specifications, you will develop and provide high-quality reference implementations that serve as benchmarks for correctness and best practices. This dual focus on clear documentation and functional code ensures that both human evaluators and AI systems can accurately understand and assess the tasks.
• Furthermore, you will play a crucial role in the quality assurance process by developing and extending unit and integration test suites. This involves creating robust validation artifacts that rigorously test the functionality and performance of the code. Your expertise will be vital in identifying edge cases, potential ambiguities in requirements, and predicting potential failure modes, thereby enhancing the overall robustness and reliability of the training data.
• Beyond task creation, you will engage in constructive peer review, meticulously examining tasks generated by other contributors. Your feedback will focus on correctness, clarity, and the overall realism of the scenarios presented. This collaborative review process is essential for maintaining a high standard across all training materials and fostering a culture of continuous improvement within the team.
• The ultimate goal of your work will be to produce high-quality, production-realistic coding tasks that are indispensable for training advanced AI models. You will deliver complete and correct reference implementations, ensuring that the code provided is not only functional but also adheres to industry best practices. Your efforts will result in robust test coverage and comprehensive validation artifacts, providing a solid foundation for AI evaluation. Additionally, your structured and actionable peer review feedback will be instrumental in guiding other contributors and refining the overall quality of the training datasets, directly impacting the effectiveness and capabilities of the AI systems being developed.
• This role is ideal for experienced software engineers who thrive on complex problem-solving and have a keen eye for detail. You will be part of a forward-thinking company dedicated to advancing AI technology through meticulously crafted training data. The team values expertise, precision, and a collaborative spirit, offering a dynamic environment where your contributions are highly valued and directly influence the success of AI initiatives.
• By participating in this project, you will gain invaluable experience in the rapidly evolving field of AI training data generation and evaluation. You will deepen your understanding of how AI models learn and how to create optimal learning materials. This role offers a unique opportunity to apply your software engineering acumen to a novel and impactful domain, expanding your professional skillset and contributing to groundbreaking technological advancements.

🎯 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.
• Experience with code reviews, refactoring, and production migrations.

🏖️ Benefits

• Fully Remote Work: Enjoy the flexibility and convenience of working from anywhere in Ecuador.
• Project-Based Flexibility: Control your own schedule and work on a project-by-project basis, allowing for a balanced work-life integration.
• Diverse Project Exposure: Engage with a variety of software engineering challenges, enhancing your skill set across different domains.
• Competitive Compensation: Paid on a per-project basis, with hourly rates estimated based on anticipated completion time, reflecting your expertise.

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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