QA Browser Test Validation Reviewer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help contributors discover projects, build a professional AI training profile, and apply in minutes. Creating an OpenTrain account is free.

• Remote contractor opportunity available worldwide
• Part-time schedule of 20+ hours per week
• English-language work
• Pay range of $30-$60 USD per hour

About AI Training and Software Evaluation

AI training is the human side of building artificial intelligence. People review examples, test model-generated outputs, and provide structured feedback that helps AI systems become more capable and reliable.

In this role, your software quality expertise will support evaluation datasets for AI-generated web applications. Your technical judgment helps determine whether a browser-testing workflow is feasible, reproducible, and clear enough to produce a dependable benchmark result.

• Contribute to the development and evaluation of modern AI systems
• Apply software quality engineering skills to AI training work
• Work remotely with flexible project participation

The Role

OpenTrain is recruiting a QA Browser Test Validation Reviewer to assess browser-based evaluation workflows for AI-generated web applications. You will examine whether browser interactions are feasible and reliable, whether test setup and fixtures are isolated, and whether assertions create deterministic, unambiguous pass or fail results.

This work combines software quality engineering, browser automation, test design, debugging, and structured feedback using project review rubrics. The role is listed as entry level and requires at least three years of relevant experience in software engineering, QA engineering, SDET, or test automation.

• Engagement type: Part-time contractor
• Time requirement: 20+ hours per week
• Pay: $30-$60 USD per hour
• Location: Worldwide
• Working language: English

What You'll Do

You will review realistic browser-based testing scenarios and determine whether each workflow can reliably support a clear evaluation result. Your feedback should identify technical weaknesses and explain whether the test logic is sufficiently isolated, reproducible, and unambiguous.

• Review browser-based testing workflows for AI-generated web applications
• Assess whether browser interactions are technically feasible and reliable
• Validate test isolation, fixtures, setup, and execution flow
• Check that assertions support reproducible and clear pass or fail outcomes
• Identify flaky tests, hidden dependencies, and ambiguous validation logic
• Provide structured technical feedback using project review rubrics

Requirements

This opportunity is suited to a careful software quality professional who can evaluate browser automation beyond whether a test appears to run. You should be able to debug failures, recognize hidden dependencies, and judge whether a workflow will produce consistent results across executions.

• At least three years of experience in software engineering, QA engineering, SDET, or test automation
• Strong experience testing modern web applications
• Experience writing automated UI and end-to-end tests
• Familiarity with Playwright, Cypress, Selenium, or a comparable browser automation framework
• Strong understanding of test isolation, fixtures, reproducibility, and reliable browser automation
• Excellent debugging skills and strong attention to detail
• Ability to identify flaky tests, hidden dependencies, and ambiguous assertions

Helpful Background

Experience evaluating realistic web application testing scenarios and applying software quality standards is useful for this work. Careful technical judgment is important when deciding whether a workflow is reliable enough to produce a clear benchmark result.

• Practical experience reviewing automated browser workflows
• A quality-focused approach to test design and validation
• Confidence explaining technical findings through structured feedback

Why Work in AI Training

AI training and data-labeling work is a fast-growing part of the technology industry. Contributors help shape how state-of-the-art AI systems behave by evaluating outputs, preparing examples, and applying specialized expertise to challenging tasks.

The work is remote and often flexible, making it possible to contribute around other commitments while building experience in an emerging field. For software professionals, projects like this offer a way to apply engineering and testing skills directly to the development of AI.

• Work from anywhere with a computer and internet connection
• Use in-demand software testing and automation expertise
• Help improve the reliability of AI-generated applications
• Build a lasting portfolio of AI training experience

How to Apply Through OpenTrain

Create a free OpenTrain account to build your profile and apply for this opportunity in minutes. OpenTrain helps you manage AI training work, show relevant experience, and discover projects that match your technical skills.

• Create or update your OpenTrain profile
• Highlight browser automation, QA, SDET, and test engineering experience
• Apply through OpenTrain for consideration as a contractor