About the Role
We are looking for an experienced and results-driven Project Manager to lead multiple AI Data Annotation Projects. This role requires exceptional project management, workflow optimization, and cross-functional coordination skills, combined with a deep understanding of data operations and code-based AI model development.
As part of our global AI team, you will collaborate with product managers, researchers, data annotation teams, and technical stakeholders to ensure the successful delivery of high-quality model training projects on time and at scale.
Key Responsibilities
1. Project Management
- Lead and manage multiple AI data annotation projects (Audio/Video/LLM), ensuring on-time delivery, quality standards, and project objectives are met.
- Track progress and milestones, identify and mitigate risks, and proactively drive solutions to ensure smooth project execution.
- Build and maintain strong collaboration with cross-functional teams, including Product, Research, Data Operations, and Engineering, to align timelines, resolve blockers, and drive project success.
2. Workflow Design & Optimization
- Design, manage, and continuously refine project workflows covering training setup, QA processes, and performance tracking.
- Partner with product managers and project leads to ensure all workflow standards align with the team's technical goals and quality benchmarks.
3. Operational Excellence
- Drive continuous improvement initiatives in data labeling, training efficiency, and quality assurance.
- Lead cross-domain optimization projects, establish best practices, and maintain process documentation, technical guides, and case manuals to ensure consistent delivery quality.
4. Data Monitoring & Analysis
- Design and implement data monitoring strategies to assess and maintain the quality of training and validation datasets.
- Utilize statistical modeling, visualization, and programming tools (Python: Pandas, NumPy, Matplotlib; SQL) to analyze annotation accuracy, dataset coverage, and model performance.
- Conduct shard-level evaluation, prompt sensitivity testing, and clustered error analysis to uncover data gaps, edge cases, and failure patterns.
- Collaborate with data and model teams to turn analytical insights into actionable strategies for training improvements and iterative optimization.
Qualifications
- Bachelor's degree or above, with 3+ years of experience in internet product operations, AI data operations.
- Strong communication and problem-solving abilities.
- Demonstrated expertise in managing complex projects and designing scalable operational workflows.
- Fluent in English, with proven ability to collaborate effectively with international teams.
- Highly adaptable to dynamic, fast-paced, and project-based environments.
- Genuine passion for AI, and computational thinking.
- Familiarity with full-stack concepts, including front-end, back-end, and database integration.
Tech-savvy, data-driven, and experienced with tools that improve project efficiency and collaboration.
