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Work From Home Remote Data Labeling information
What is the difference between Work From Home Remote Data Labeling vs Work From Home Remote Data Annotation?
| Aspect | Work From Home Remote Data Labeling | Work From Home Remote Data Annotation |
|---|---|---|
| Primary Task | Labeling data such as images, videos, or text for machine learning | Annotating data with detailed tags or notes for AI training |
| Required Skills | Basic understanding of data types, attention to detail | Similar skills, often requiring more specific annotation tools knowledge |
| Work Environment | Remote, flexible hours, online platforms | Remote, similar environment, often on the same platforms |
| Industry Usage | Common in AI and machine learning sectors | Used in AI, computer vision, NLP projects |
Both roles involve remote data work for AI training, with slight differences in task complexity and terminology. Data labeling generally refers to broad categorization, while data annotation involves detailed tagging. They are often used interchangeably but may vary by employer.

Contractor
Posted 18 days ago
Job description
We've grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms.
Reducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital.
The Opportunity
As Data Labeling Lead, you'll play a key role in leading and managing our in-house data labeling team to ensure the highest quality of training data for our models. You'll collaborate closely with the ML and engineering teams to refine labeling guidelines and maintain rigorous accuracy standards. This is a high-impact role where you'll help shape the foundation of our AI capabilities from the ground up.
What You'll Do:
- Lead, train, and manage our in-house data labeling team.
- Define, execute, and continuously improve data annotation processes with a very high attention to detail.
- Ensure high-quality data outputs and meet rigorous accuracy and consistency standards.
- Work closely with ML engineers to understand data requirements and edge cases.
- Manage team schedules, specifically coordinating and working nighttime hours Pacific Time (PT).
- Possess a very high attention to detail.
- Have 3+ years of experience working in Python and are comfortable managing basic data labeling apps.
- Have the ability to work nighttime hours PT.
- Hold yourself to a high bar for quality and precision.
- Enjoy solving complex problems and building from first principles.
- Have 3+ years of experience in data labeling, operations, or team management.
- Operate well in fast-changing, high-growth environments.
- Collaborate effectively across technical and non-technical teams.
- Take full ownership from strategy through execution.
- Have experience at an early-stage or high-growth startup.
- Are familiar with AI/ML data pipelines and labeling tools.
- Care deeply about combining operational excellence with business impact.
- Impact: Your work directly shapes how the world's best AI companies access and use enterprise data.
- Speed: We move fast, ship often, and iterate in days, not months.
- Learning: Work alongside world-class engineers, operators, and founders who care deeply about product, precision, and velocity.
This is a contract role based anywhere in North America. We're an early-stage company, we move fast and work hard. Please apply only if that excites you.
Equal Opportunity
Reducto is an Equal Opportunity Employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration without regard to sex, race, color, age, national origin, religion, disability, sexual orientation, gender identity, veteran status, or any other protected category.