[Data] AI Data Labeling Manager
👋 About the Team
The Data Team at Nota designs and operates the end-to-end process of acquiring, managing, and delivering datasets used for AI model training, validation, and testing. To ensure safe and high-quality datasets that meet project-specific requirements, we work closely with cross-functional teams, including Research & Development, Infrastructure, and Legal.
By defining standards and workflows that connect AI datasets to actual product value, we execute an efficient data lifecycle—contributing directly to the reliability and quality of our AI products.
📌 What You’ll Do at This Position
You will take the lead on managing data labeling projects that support product R&D. This includes overseeing incoming datasets according to internal policies and coordinating both in-house labeling tasks and outsourced projects. You’ll work closely with planners and engineers to translate product requirements into datasets.
Beyond the initial labeling phase, you’ll continuously evaluate how datasets should be designed and maintained to reflect the fast-evolving AI industry and internal priorities.
✅ Key Responsibilities
- Plan and manage data labeling projects
- Define task requirements and manage guideline documentation
- Manage timelines, budgets, and communication with internal and external stakeholders
- Oversee deliverables and ensure quality control
- Coordinate contracts and payments for in-house labelers
- Operate and manage labeling platforms
- Manage subscription-based or open-source platforms (e.g., CVAT, Label Studio)
- Improve workflows and enhance labeling efficiency
- Execute internal data management tasks
- Classify datasets and manage access control on S3 in line with internal policies
- Document workflows and status via Jira, Confluence, and Notion
✅ Requirements
- Eligible for overseas travel
- 3–5 years of hands-on experience planning and managing data processing projects (including schedule, budget, and risk management)
- Strong communication and collaboration skills with Infra/DevOps/ML engineers, especially in cloud or server environments
- Proficient in written documentation and problem-solving through structured communication
✅ Pluses
- Bachelor’s degree or higher in a relevant field
- Proficiency with spreadsheet queries for data mapping and systematic documentation
- Experience managing or building open-source labeling platforms (e.g., CVAT, Label Studio)
- Experience working with vision datasets, personal data, or medical datasets
✅ Hiring Process
- Document Screening → Screening Interview → 1st Interview → 2nd Interview → Final Decision
(Additional tasks may be requested during the process.)
🤓 A Message from the Team
As a member of the Data Team, you’ll gain practical insight into how AI datasets—one of Nota’s core assets—impact model performance and technological progress. You’ll take ownership of dataset building and management tasks, and collaborate with teammates from diverse backgrounds to shape data into a strategic asset.
You won’t be limited to a narrow scope like data collection or platform ops; instead, you’ll experience the full AI dataset lifecycle. This involves close collaboration with Infra, Legal, and R&D teams. Through this end-to-end exposure, you’ll develop a broad perspective on how data connects directly to product value and evolve as a true data operations expert.
Please Check Before Applying! 👀
- This job posting is open continuously, and it may close early upon completion of the hiring process.
- Resumes that include sensitive personal information, such as salary details, may be excluded from the review process.
- Providing false information in the submitted materials may result in the cancellation of the application.
- Please be aware that references will be checked before finalizing the hiring decision.
- Compensation will be discussed separately upon successful completion of the final interview.
- There will be a probationary period after joining, and there will be no discrimination in the treatment during this period.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
🔎 Helpful materials
[Data] AI Data Labeling Manager
👋 About the Team
The Data Team at Nota designs and operates the end-to-end process of acquiring, managing, and delivering datasets used for AI model training, validation, and testing. To ensure safe and high-quality datasets that meet project-specific requirements, we work closely with cross-functional teams, including Research & Development, Infrastructure, and Legal.
By defining standards and workflows that connect AI datasets to actual product value, we execute an efficient data lifecycle—contributing directly to the reliability and quality of our AI products.
📌 What You’ll Do at This Position
You will take the lead on managing data labeling projects that support product R&D. This includes overseeing incoming datasets according to internal policies and coordinating both in-house labeling tasks and outsourced projects. You’ll work closely with planners and engineers to translate product requirements into datasets.
Beyond the initial labeling phase, you’ll continuously evaluate how datasets should be designed and maintained to reflect the fast-evolving AI industry and internal priorities.
✅ Key Responsibilities
- Plan and manage data labeling projects
- Define task requirements and manage guideline documentation
- Manage timelines, budgets, and communication with internal and external stakeholders
- Oversee deliverables and ensure quality control
- Coordinate contracts and payments for in-house labelers
- Operate and manage labeling platforms
- Manage subscription-based or open-source platforms (e.g., CVAT, Label Studio)
- Improve workflows and enhance labeling efficiency
- Execute internal data management tasks
- Classify datasets and manage access control on S3 in line with internal policies
- Document workflows and status via Jira, Confluence, and Notion
✅ Requirements
- Eligible for overseas travel
- 3–5 years of hands-on experience planning and managing data processing projects (including schedule, budget, and risk management)
- Strong communication and collaboration skills with Infra/DevOps/ML engineers, especially in cloud or server environments
- Proficient in written documentation and problem-solving through structured communication
✅ Pluses
- Bachelor’s degree or higher in a relevant field
- Proficiency with spreadsheet queries for data mapping and systematic documentation
- Experience managing or building open-source labeling platforms (e.g., CVAT, Label Studio)
- Experience working with vision datasets, personal data, or medical datasets
✅ Hiring Process
- Document Screening → Screening Interview → 1st Interview → 2nd Interview → Final Decision
(Additional tasks may be requested during the process.)
🤓 A Message from the Team
As a member of the Data Team, you’ll gain practical insight into how AI datasets—one of Nota’s core assets—impact model performance and technological progress. You’ll take ownership of dataset building and management tasks, and collaborate with teammates from diverse backgrounds to shape data into a strategic asset.
You won’t be limited to a narrow scope like data collection or platform ops; instead, you’ll experience the full AI dataset lifecycle. This involves close collaboration with Infra, Legal, and R&D teams. Through this end-to-end exposure, you’ll develop a broad perspective on how data connects directly to product value and evolve as a true data operations expert.
Please Check Before Applying! 👀
- This job posting is open continuously, and it may close early upon completion of the hiring process.
- Resumes that include sensitive personal information, such as salary details, may be excluded from the review process.
- Providing false information in the submitted materials may result in the cancellation of the application.
- Please be aware that references will be checked before finalizing the hiring decision.
- Compensation will be discussed separately upon successful completion of the final interview.
- There will be a probationary period after joining, and there will be no discrimination in the treatment during this period.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
🔎 Helpful materials