Overview
We are looking for a results-driven Project Manager to oversee large-scale LLM AI data annotation operations. The Project Manager will ensure projects are delivered on time, at target quality, and with optimized productivity, supporting the development of advanced Large Language Models (LLMs) and multimodal AI systems.
Key Responsibilities
- Manage end-to-end delivery of LLM projects.
- Plan resources, track milestones, and drive daily operations to meet throughput and turnaround targets.
- Ensure project KPIsAccuracy 90%, Consistency 95%, Rejection Rate 10%are consistently achieved.
- Establish and maintain QA workflows, calibration sessions, and retraining programs.
- Monitor and report key metrics: accuracy, productivity, quality trends, and rejection causes.
- Lead, mentor, and evaluate team leads, QA reviewers, and annotators to achieve continuous improvement.
- Communicate clearly with internal and client stakeholders; escalate issues with actionable solutions.
- Drive process improvement initiatives using Six Sigma / Kaizen principles for efficiency and quality optimization.
Qualifications
Required:
- Bachelor's degree in STEM, Data Science, Psychology, Linguistics, Project Management, or a related field.
- 35 years of experience managing large-scale data or AI-related projects.
- Strong understanding of KPI-driven operations, quality management, and data workflows.
- Excellent analytical, organizational, and communication skills.
- Proficiency in project management tools (Airtable, Jira, Smartsheet, Excel/Google Sheets).
Preferred:
- Experience in AI data annotation, machine learning, or RLHF projects.
- Knowledge of multimodal data operations (text/audio/video).
- Certified Six Sigma Green Belt or Kaizen practitioner.
- Familiarity with data visualization or scripting (Power BI, SQL, Python) is an advantage.
Core Competencies
- Operational Leadership: Strong execution and team management under defined metrics.
- Quality Focus: Commitment to maintaining data precision and consistency.
- Data-Driven Execution: Uses structured analysis to guide improvement.
- Continuous Improvement: Applies process excellence methodologies (Six Sigma / Kaizen).
- Strategic Communication: Clear and professional coordination across teams and stakeholders.
Purpose of the Role
This position ensures that every annotated dataset delivered meets the highest standards of accuracy, efficiency, and consistency, directly contributing to the creation of more intelligent and emotionally adaptive AI systems.
