Project Manager, AI Data

Responsibilities

• End-to-End Delivery: Manage the full lifecycle of AI data projects, from scoping and guidelines creation to data delivery and post-mortem analysis.
• Pipeline Management: Oversee large-scale data pipelines for multilingual data collection (audio, text, image) and LLM evaluation (RLHF, SFT, ranking, and safety testing).
• Resource Planning: Forecast capacity needs and manage the allocation of internal and external workforce (vendors, crowdsourced contributors) across multiple time zones and languages.
• KPI Tracking: Rigorously monitor and report on key performance indicators, including: Throughput, Quality, and Productivity.
• Quality Control: Implement robust QA loops, root-cause analysis for quality dips, and corrective training for annotator pools.
• Dashboards: Build and maintain dashboards to visualize project health and flag bottlenecks in real-time.
• Global Coordination: Manage relationships with data experts and crowd pools, ensuring adherence to SLAs regarding localized nuances and linguistic accuracy.
• Cross-Functional Collaboration: Liaise with Applied AI Technical Ops teams. Translate technical requirements into clear, actionable guidelines for non-technical annotators.
• Feedback Loops: Facilitate continuous feedback loops where data insights drive updates to annotation guidelines and model fine-tuning strategies.

Requirements

• Experience: 3-5+ years of project management experience, specifically within AI/ML data operations.
• LLM Knowledge: Strong understanding of LLM training processes (Pre-training, SFT, RLHF) and evaluation methodologies (Human-in-the-loop, red teaming).
• Data Proficiency: Advanced proficiency in Excel/Google Sheets; ability to write SQL queries to extract and analyze performance data.
• Methodology: Proven track record using Agile, Scrum, or Kanban methodologies to manage complex workflows.
• Communication: Exceptional ability to write clear, unambiguous guidelines for multilingual audiences.

Preferred Qualifications

• Multilingual: Fluency in a second language is highly desirable.
• Technical Tools: Experience with data annotation platforms (e.g. Scale AI, Super Annotate) and project management tools (e.g. Jira).
• Education: Background in ML Engineering, Computer Science, Data Science and Project Management training.

Benefits

• Remote Work: Work from anywhere, any time you want.
• Competitive Pay: Earn money quickly and fairly.
• Professional Growth: Build your professional network in a supportive community.
• Streamlined Process: Apply through a tailored process based on your expertise.

About the Company

LILT's mission is to make the world's information available to everyone, no matter the language they speak. Join our global community who thrive on innovation and excellence. Our collective knowledge, uniqueness, and skills deliver multilingual AI and human-verified services to Enterprises, Governments, and AI Developers around the world.