Project Manager (Applied AI)

Join our team as a Project Manager (Applied AI) where you will lead large-scale multilingual data collection and Large Language Model (LLM) evaluation initiatives. You will manage the full lifecycle of AI data projects, oversee large-scale data pipelines, track key performance indicators, and coordinate globally with data experts and crowd pools. You will also collaborate cross-functionally with Applied AI Technical Ops teams and facilitate continuous feedback loops. Benefits include medical coverage, paid parental leave, a monthly lifestyle benefit stipend, meaningful equity, 401(k) matching, and flexible time off.

• Manage the full lifecycle of AI data projects, from scoping and guidelines creation to data delivery and post-mortem analysis.
• Oversee large-scale data pipelines for multilingual data collection and LLM evaluation, ensuring adherence to SLAs regarding localized nuances and linguistic accuracy.
• Monitor and report on key performance indicators, including throughput, quality, and productivity, while maintaining dashboards to visualize project health.

• If you thrive in a fast-paced environment where you can optimize workflows for productivity, quality, and throughput, we want to hear from you
• 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
• Data Proficiency: Advanced proficiency in Excel/Google Sheets; ability to write SQL queries to extract and analyze performance data
• LLM Knowledge: Strong understanding of LLM training processes (Pre-training, SFT, RLHF) and evaluation methodologies (Human-in-the-loop, red teaming)
• Experience: 3-5+ years of project management experience, specifically within AI/ML data operations
• Technical Tools: Experience with data annotation platforms (e.g. Scale AI, Super Annotate) and project management tools (e.g. Jira)
• Multilingual: Fluency in a second language is highly desirable
• Education: Background in ML Engineering, Computer Science, Data Science and Project Management training