Large Language Model Data Base Head
Active AI foundation-model company offering multimodal models, consumer AI products, and an enterprise/developer API platform.
Funding history
About MiniMax Group Inc.
MiniMax develops proprietary multimodal foundation models spanning language, video, speech, and music, and operates AI-native products including MiniMax Agent, MiniMax Design, MiniMax Audio, Talkie, Hailuo AI, and an Open Platform.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead the overall operation of the data base, coordinating capacity, staffing, project schedules, and on-site resources. You will turn large language model training, evaluation, and content-safety needs into annotation standards, workflows, and acceptance criteria. You will manage hiring, training, performance, vendors, quality systems, operational metrics, data security, delivery risks, and staffing risks.
Requirements
- Bachelor's degree or above
- 5+ years of experience in data annotation, content review, or AI training
- Experience managing teams of more than 100 people
- Knowledge of large language model training and evaluation workflows
- Understanding of SFT, preference-data, and multimodal-data production and quality requirements
- Ability to deliver large-scale projects while coordinating resources, quality, schedule, and cost
- Team development and vendor-management experience
- Strong data-analysis and cross-functional collaboration skills
- Ability to identify operational issues and drive improvements
- Ability to work long term at the base location
Responsibilities
- Lead overall data base operations, including capacity, staffing, and project scheduling
- Own data delivery quality, efficiency, and cost
- Translate model training and evaluation needs into annotation standards, workflows, and acceptance criteria
- Translate content-safety needs into safety standards, workflows, and acceptance criteria
- Manage recruiting, training, performance, and management-pipeline development
- Manage vendors and support team stability and business expansion
- Improve quality-management and operational-metric systems
- Increase productivity through process optimization, tools, and human-machine collaboration
- Coordinate on-site operations and support resources
- Implement data-security requirements and manage delivery and staffing risks