Polish Data Annotator, Product Review Topics & Sentiment
About OpenTrain and This Opportunity
OpenTrain AI is hiring contractors to do vital human-in-the-loop work that helps AI systems understand real-world language. OpenTrain is the #1 platform for careers in AI training and data labeling, and this role is a direct chance to join that fast-growing field.
This listing is for an ongoing Polish-language annotation project focused on product reviews. Work is remote and flexible, making it well suited to people who need adaptable hours while doing meaningful work that improves AI quality.
- Role type: contractor, part-time
- Data type: text (Polish product reviews)
- Label type: classification — topics and sentiment
About AI Training Work
AI training (also called data labeling or annotation) is the human side of building intelligent systems: people prepare and check examples that models learn from. Contributors directly shape how models read reviews, detect product features, and surface useful insights for shoppers and businesses.
This work is especially accessible: many projects need language fluency and attention to detail rather than advanced technical skills, and they offer flexible, remote schedules.
- Flexible, remote work you can do from anywhere
- Entry and intermediate opportunities across many domains
The Role
You will review Polish product reviews and confirm or correct the topics and sentiment labels assigned to product features mentioned in each review. The goal is to improve AI models that classify review content by topic (for example: product quality, battery life, usability) and sentiment (positive, negative, neutral).
Compensation is USD 7.00 per hour. This project requires a minimum commitment of 15 hours per week and offers a flexible schedule under an ongoing contractor arrangement.
- Hourly pay: $7.00 USD per hour
- Minimum weekly commitment: 15 hours (flexible scheduling)
- Employment types: contractor, part-time
What You'll Do Day to Day
Your primary responsibility is accurate, consistent labeling of Polish-language product reviews so models learn to detect topics and sentiment tied to specific product features.
- Read Polish product reviews and identify mentioned product features and topics
- Confirm or correct topic labels (e.g., product quality, features, value)
- Assign or verify sentiment labels for each feature mention: positive, negative, or neutral
- Follow project guidelines and quality standards to ensure consistent annotations
- Work independently to meet daily or weekly labeling targets and deadlines
Requirements
To be successful in this role you must meet the language, availability, and basic tooling requirements below.
- Native or fluent Polish speaker
- Experience in data annotation, labeling, or a similar role (intermediate level)
- Strong attention to detail and accuracy when reviewing and labeling text
- Ability to commit at least 15 hours per week with a flexible schedule
- Reliable internet connection and access to a computer or necessary tools
- Dependable, able to meet deadlines and work independently
- Familiarity with e-commerce, especially consumer electronics, home goods, or personal care, is a plus (not required)
Who Should Apply
Apply if you are a Polish speaker who enjoys careful, structured work and wants flexible, remote part-time contract work that contributes directly to real AI systems.
- Detail-oriented annotators with prior labeling experience
- People familiar with reading product reviews and product terminology
- Contractors who can reliably deliver 15+ hours per week
How To Apply and What To Expect
Create an OpenTrain account and apply for this project to be considered. OpenTrain AI is the hiring organization for this role, and qualified applicants will receive project instructions, labeling guidelines, and onboarding materials to get started.
Expect to work remotely on text classification tasks, follow provided quality guidelines, and communicate with the project team when clarification is needed.
- Apply via your OpenTrain account
- Onboarding includes guidelines and examples to ensure consistent labeling
- Ongoing work with expectations for quality and deadlines