Background information about the job or company (e.g., role context, company overview)

DDD believes talent has no boundaries--and opportunities shouldn’t either. In 2001, we saw the need to bring tech skills and living-wage work to men and women in underserved communities in Asia. It was here that DDD helped plant the seed for a socially responsible outsourcing practice known as impact sourcing.

Responsibilities or duties

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.

Qualifications or requirements (e.g., education, skills)

Bachelor’s degree in Computer Science, Information Systems, Engineering, Data/AI, Business Operations, or a related field.

Experience needed

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.

Any other provided details (e.g., benefits, work environment, team info, or additional notes)

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.

• 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.
• 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.
• 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.
• 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.
• 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.

• AI/ML data operations
• 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
• Annotation platforms such as Deepen, Segment, Kognic, Dataloop, CVAT, or similar tools

• 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.