We are looking for a Data Annotation Coordinator to join our AI team to oversee the entire data annotation process, supporting our AI and machine learning initiatives. In this role, you will be central to ensuring the efficiency, accuracy, and success of our data labeling processes.
If it sounds interesting to you, then look no further — send us your CV!
In this role, you will:
- Organize and supervise the data annotation process, ensuring its accuracy and quality
- Research, identify, and implement data annotation tools and solutions for diverse tasks
- Purchase pre-annotated data when required and develop internal tools for data labeling as necessary
- Build and lead the data annotation team, managing cooperation with external freelancers, including searching, selecting, and organizing cooperation with freelancers to meet the organizational needs
- Coordinate team tasks and workflows to meet project timelines and deliverables
- Collaborate closely with the AI team to align data annotation efforts with machine learning model requirements and understand the neural network training process
- Implement quality control measures and conduct regular audits to maintain high annotation standards
- Develop and maintain annotation guidelines and documentation to ensure consistency and accuracy across the team
- Ensure compliance with data privacy and security regulations throughout the data annotation process
Skills you’ll need to bring:
- Proven experience in managing data annotation processes and leading annotation teams
- Comprehensive knowledge of data labeling processes and familiarity with relevant tools, platforms, and best practices in the data annotation field
- Familiarity with machine learning, neural networks, and the role of annotated data in training AI models
- Prior experience working with or managing external freelancers or data labeling vendors
- Strong understanding of project management methodologies and tools to support deadline-driven environments
- Strong leadership, communication, and organizational skills with the ability to convey technical aspects to both technical and non-technical stakeholders
- Experience with quality assurance processes for large datasets
- Keen attention to detail and the ability to balance multiple projects and priorities simultaneously
- Experience with data privacy regulations and ethical considerations in data annotation
- Strong analytical skills to monitor processes and implement improvements based on data-driven insights.
- Ability to develop and implement data quality metrics and KPIs to measure the effectiveness of annotation processes
- Upper-intermediate level of English