Global AI Data Operations Project Manager

Openkrill; United States; Remote; USD 110,000 - 180,000; Full time

Job summary

LILT is seeking a data-driven Project Manager to lead large-scale multilingual data collection and LLM evaluation initiatives. You will orchestrate global teams of annotators and data specialists as the operational backbone of AI development.

Join a fast-paced environment focused on productivity, quality, and throughput, with opportunities to optimize workflows and impact enterprise language tech.

Qualifications

• 3-5+ years of project management experience in AI/ML data operations.
• Strong understanding of LLM training processes (Pre-training, SFT, RLHF) and evaluation methods (HIT).
• Advanced proficiency in Excel/Google Sheets; ability to write SQL queries for data analysis.
• Experience with Agile, Scrum or Kanban to manage complex workflows.
• Excellent ability to write clear guidelines for multilingual audiences.

Responsibilities

• End-to-End Delivery: manage full lifecycle from scoping to post-mortem analysis.
• Pipeline Management: oversee multilingual data pipelines and LLM evaluation.
• KPI Tracking: monitor throughput, quality, productivity, and costs.
• Quality Control: run QA loops and corrective training for annotators.
• Dashboards: maintain dashboards to visualize project health in real-time.
• Stakeholder Management: coordinate with data experts and cross-functional teams.
• Feedback Loops: drive updates to guidelines and model fine-tuning.

Skills

Project management

AI/ML data ops

Excel/SQL

Agile-Scrum-Kanban

Clear multilingual guidelines

Education

ML Engineering/CS/Data Science background

PM training

Tools

Jira

Scale AI

Super Annotate

Job description

LILT is seeking a data-driven Project Manager to lead large-scale multilingual data collection and LLM evaluation initiatives. You will orchestrate global teams of annotators and data specialists as the operational backbone of AI development.

Join a fast-paced environment focused on productivity, quality, and throughput, with opportunities to optimize workflows and impact enterprise language tech.