Digital Divide Data (DDD) is a BPO that delivers ML data solutions and content services to Fortune 500 companies and the world’s leading academic institutions. DDD is unique in its ability to deliver end-to-end data creation, curation, labeling, and annotation services, regardless of scale, with a guaranteed level of quality.

Client Partnership & Solutioning

• Support client discovery sessions to understand dataset needs, workflow rules, and ML objectives.
• Translate client requirements into workflows, annotation guidelines, taxonomies, and quality frameworks.
• Provide clients with delivery updates, performance insights, and workflow recommendations.
• Support solution scoping, demos, proposal inputs, and client clarifications.
• Identify opportunities to improve or expand existing programs.

Program Delivery Management

• Oversee daily execution of assigned AI/ML, Computer Vision, AV/ADAS, and related data workflows.
• Ensure delivery against agreed KPIs, SLAs, accuracy, throughput, quality, and timelines.
• Manage onboarding, calibration, guideline updates, workflow transitions, and production readiness.
• Work with Delivery Leads to ensure staffing, training, tool readiness, and operational consistency.
• Maintain accurate documentation and clear process controls across teams.

Quality, Analytics & Performance Management

• Build and maintain reports and dashboards to track accuracy, productivity, error trends, latency, and overall program performance.
• Conduct root-cause analysis for quality issues and work with QA and Training teams to implement corrective actions.
• Use data insights to improve annotation quality, reduce rework, and strengthen delivery outcomes.
• Present clear performance updates to clients and internal stakeholders.

Cross-Functional Collaboration

• Partner with QA, Training, Delivery, Technical Operations, Business Development, and client-facing teams.
• Support pilot setup, workflow testing, guideline refinement, schema changes, and ontology updates.
• Ensure delivery teams understand and apply updated instructions and quality standards.

Continuous Improvement

• Recommend workflow improvements based on data trends, client feedback, and team input.
• Support automation opportunities such as pre-labeling, AI-assisted annotation, QC automation, and improved audit methods.
• Promote consistent ways of working, strong calibration practices, and continuous improvement across programs.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data/AI, Business Operations, or a related field.
• Minimum 5 years of relevant experience in AI/ML operations, data annotation, technical delivery, program management, BPO, or related operational environments.
• Experience managing or supporting annotation workflows, AI data pipelines, computer vision, AV/ADAS, robotics, or autonomous systems is highly preferred.
• Proven experience working in client-facing, KPI-led technical delivery environments.
• Experience leading teams, managing escalations, improving workflows, and delivering against quality and productivity targets.

The successful candidate should have strong working knowledge of AI/ML data operations, including some or all of the following:

• 2D and 3D Computer Vision annotation
• NLP workflows
• LiDAR and RADAR datasets
• AV/ADAS data workflows
• Robotics or autonomous systems data
• Data quality and its impact on machine learning model performance

Experience with annotation platforms such as Deepen, Segment, Kognic, Dataloop, CVAT, or similar tools is preferred.