We are looking for a Data Annotation (Labeling) Team Lead to join our AI team to oversee the entire data annotation process, supporting our AI and machine learning initiatives. This role requires strong leadership skills combined with a good understanding of data collection and annotation for machine learning models.
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
- Build and lead the data annotation team, coordinate team tasks and workflows, foster the team development
- Implement quality control processes, analyze errors, and improve standards
- Develop and maintain annotation guidelines and documentation to ensure consistency and accuracy across the team
- Optimize annotation processes and explore automation opportunities
- Closely collaborate with data engineers to develop efficient data processing solutions and tools, implement automated data processing workflows to streamline annotation processes
- Collaborate closely with ML Engineers to align data annotation efforts with machine learning model requirements and understand the neural network training process
- Take part in cross-functional coordination and cooperation with other colleagues
- Manage costs related to data sourcing and annotation
- Explore outsourcing & alternative data solutions, manage cooperation with external freelancers and partners, including searching, selecting, and organizing cooperation with them to meet the organizational needs
- Ensure compliance with data privacy and security regulations throughout the data annotation process
Skills you’ll need to bring:
- Proven experience leading a data annotation team
- Basic understanding of AI/ML concepts (data annotation needs, task types, neural network training)
- Good knowledge of data labeling processes and familiarity with relevant tools, platforms, and best practices in the data annotation field
- Basic understanding of data collection processes (web scraping, dataset management)
- 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
- Experience managing budgets & external partnerships
- Upper-intermediate level of English