Program Manager, Annotations at Motive (2022-04 – Present)
Oversee the full lifecycle of both live and offline AI data annotation projects from initial planning to final delivery. Lead a multi-layered team of over 320 members including team leads, associate managers, and coordinators. Serve as the primary bridge between the annotations team and departments like Operations, Product, R&D, HR, and Tech Support.
- Program Leadership & Strategy: Oversee the full lifecycle of both live and offline AI data annotation projects from initial planning to final delivery, ensuring that high-quality, structured data is delivered to Customers, R&D and Product teams on time. Align team goals with broader organizational OKRs.
- Project Planning & Execution: Work closely with internal stakeholders to understand annotation needs and turn them into actionable project plans. Define clear scopes, set timelines, allocate resources, and manage execution.
- Cross-Functional Collaboration: Serve as the primary bridge between the annotations team and departments like Operations, Product, R&D, HR, and Tech Support. Ensure open lines of communication and resolve roadblocks quickly.
- Team Leadership & Growth: Lead a multi-layered team of over 320 members including team leads, associate managers, and coordinators. Foster a culture of ownership, accountability, and growth.
- Process Development & Optimization: Build and refine scalable processes for recruitment, onboarding, training, task assignment, annotation, and quality assurance.
- Scaling & Remote Operations: Scaled the team from 20 to over 320 members. Successfully transitioned the entire team to remote work during COVID.
- Reporting & Insights: Track progress and team performance through dashboards and regular reporting. Provide actionable insights to leadership.
- Customer-Focused Delivery: Partnered with technical support and product teams to resolve client escalations swiftly and effectively. Maintained high levels of customer satisfaction.
Project Coordinator – AI Data Projects at Motive (2018-10 – 2022-04)
Collaborated with cross-functional stakeholders to define project scope, success metrics, and expected deliverables for AI data annotation tasks. Analyzed project requirements and translated them into detailed execution plans.
- Collaborated with cross-functional stakeholders, including R&D teams, to define project scope, success metrics, and expected deliverables for AI data annotation tasks.
- Analyzed project requirements and translated them into detailed execution plans with clear timelines, milestones, and resource estimates.
- Locked project timelines and deliverables with points of contact (POCs), ensuring alignment between internal capabilities and external expectations.
- Allocated resources efficiently based on project complexity, priority, and skill requirements, balancing capacity with deadlines.
- Developed and implemented structured annotation workflows, quality assurance mechanisms, and review processes to ensure high-quality, scalable data output.
- Conducted daily and weekly progress tracking, maintained documentation, and escalated blockers in a timely manner to keep projects on schedule.
- Delivered clean, validated datasets to R&D teams for training, testing, or validation of AI models.
