Location:Remote (India) Employment Type: Full-Time Shift: Overlap with US Business Hours Joining Requirement: Immediate Joiners Preferred Visa Requirement: Valid US Business Visa (Mandatory)
About the Role
We are looking for an experienced Annotation Lead to drive end-to-end data annotation operations for AI/ML programs. The ideal candidate will be responsible for managing annotation workflows leading distributed teams and vendors ensuring data quality and delivering high-quality labeled datasets at scale. This role requires a strong blend of operational leadership annotation expertise and quality governance.
Key Responsibilities
Annotation Operations & Delivery
Lead and manage large-scale annotation projects across image video and multimodal datasets.
Plan prioritize and monitor annotation workloads to ensure timely delivery.
Coordinate with stakeholders data scientists and engineering teams to understand project requirements and translate them into executable annotation workflows.
Identify operational bottlenecks and implement process improvements to increase efficiency and throughput.
Tool & Platform Management
Hands-on experience with any one leading annotation platform such as SuperAnnotate Labelbox Scale AI CVAT V7 or equivalent.
Configure projects workflows user roles review pipelines and quality checkpoints.
Manage dataset imports/exports and support integration requirements where needed.
Drive platform adoption and best practices across annotation teams.
Workforce & Vendor Management
Manage internal annotators and external vendor teams.
Track productivity utilization SLA adherence and operational performance.
Establish performance metrics and drive continuous improvement initiatives.
Conduct team training calibration sessions and performance reviews.
Data Quality & Governance
Define and monitor annotation quality standards.
Implement quality assurance processes audits and validation frameworks.
Measure annotation consistency using metrics such as Inter-Annotator Agreement (IAA) Consensus Scoring Cohens Kappa or similar quality measures.
Develop gold-standard datasets and corrective action plans to improve quality outcomes.
Documentation & Training
Create clear annotation guidelines SOPs and training materials.
Translate technical requirements into easy-to-understand labeling instructions.
Conduct onboarding and continuous training for annotation teams.
Required Qualifications
Bachelors degree in Computer Science Engineering Data Science Information Technology or related field.
6 years of experience in Data Annotation AI Operations Data Labeling or ML Data Programs.
Hands-on experience with at least one annotation platform (SuperAnnotate Labelbox Scale AI CVAT V7 or equivalent).
Experience managing annotation teams workforce operations or vendor partners.
Strong understanding of annotation quality frameworks and review processes.
Knowledge of image video and multimodal annotation techniques.
Excellent communication stakeholder management and problem-solving skills.
Ability to work independently in a remote environment.
Preferred Qualifications
Experience supporting Computer Vision Generative AI or Machine Learning projects.
Exposure to semantic segmentation object detection object tracking OCR LiDAR or 3D annotation projects.
Basic knowledge of Python APIs JSON XML or CSV data formats.
Experience managing globally distributed teams.
Required Experience:
Staff IC
Experience level - 8-14 yearsJob Description Annotation LeadLocation:Remote (India) Employment Type: Full-Time Shift: Overlap with US Business Hours Joining Requirement: Immediate Joiners Preferred Visa Requirement: Valid US Business Visa (Mandatory)About the RoleWe are looking for an experienced A...
Experience level - 8-14 years
Job Description Annotation Lead
Location:Remote (India) Employment Type: Full-Time Shift: Overlap with US Business Hours Joining Requirement: Immediate Joiners Preferred Visa Requirement: Valid US Business Visa (Mandatory)
About the Role
We are looking for an experienced Annotation Lead to drive end-to-end data annotation operations for AI/ML programs. The ideal candidate will be responsible for managing annotation workflows leading distributed teams and vendors ensuring data quality and delivering high-quality labeled datasets at scale. This role requires a strong blend of operational leadership annotation expertise and quality governance.
Key Responsibilities
Annotation Operations & Delivery
Lead and manage large-scale annotation projects across image video and multimodal datasets.
Plan prioritize and monitor annotation workloads to ensure timely delivery.
Coordinate with stakeholders data scientists and engineering teams to understand project requirements and translate them into executable annotation workflows.
Identify operational bottlenecks and implement process improvements to increase efficiency and throughput.
Tool & Platform Management
Hands-on experience with any one leading annotation platform such as SuperAnnotate Labelbox Scale AI CVAT V7 or equivalent.
Configure projects workflows user roles review pipelines and quality checkpoints.
Manage dataset imports/exports and support integration requirements where needed.
Drive platform adoption and best practices across annotation teams.
Workforce & Vendor Management
Manage internal annotators and external vendor teams.
Track productivity utilization SLA adherence and operational performance.
Establish performance metrics and drive continuous improvement initiatives.
Conduct team training calibration sessions and performance reviews.
Data Quality & Governance
Define and monitor annotation quality standards.
Implement quality assurance processes audits and validation frameworks.
Measure annotation consistency using metrics such as Inter-Annotator Agreement (IAA) Consensus Scoring Cohens Kappa or similar quality measures.
Develop gold-standard datasets and corrective action plans to improve quality outcomes.
Documentation & Training
Create clear annotation guidelines SOPs and training materials.
Translate technical requirements into easy-to-understand labeling instructions.
Conduct onboarding and continuous training for annotation teams.
Required Qualifications
Bachelors degree in Computer Science Engineering Data Science Information Technology or related field.
6 years of experience in Data Annotation AI Operations Data Labeling or ML Data Programs.
Hands-on experience with at least one annotation platform (SuperAnnotate Labelbox Scale AI CVAT V7 or equivalent).
Experience managing annotation teams workforce operations or vendor partners.
Strong understanding of annotation quality frameworks and review processes.
Knowledge of image video and multimodal annotation techniques.
Excellent communication stakeholder management and problem-solving skills.
Ability to work independently in a remote environment.
Preferred Qualifications
Experience supporting Computer Vision Generative AI or Machine Learning projects.
Exposure to semantic segmentation object detection object tracking OCR LiDAR or 3D annotation projects.
Basic knowledge of Python APIs JSON XML or CSV data formats.