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Data Labeling Project Manager : 26-00284

Remote, CA

Posted: 02/02/2026 Job Category: Project / Program / Product Management & Architecture Job Number: 27364362 Country: US

Job Description

Primary Skills: Project Management - Expert, Machine Learning - Intermediate, Data Analysis - Advanced, Vendor Management - Intermediate, LLM - Expert.
Contract Type: W2
Duration: 11+ Months
Location: #LI - Remote
Pay Range: $42.35 - $47.35 per hour on W2
#LP

Job Summary: 
Data Labeling Project Manager with a strong focus on growth and innovation as we venture into new international markets. The ideal candidate will spearhead our content relevance and quality initiatives, leveraging human judgment and cutting-edge AI tools, and managing large-scale evaluation programs in collaboration with cross-functional teams and external data labeling vendors. This role is pivotal in delivering precise, actionable insights to enhance our platform's user experience worldwide.

Key Responsibilities:

  • Collaborate with internal stakeholders across various disciplines to understand and fulfill their data evaluation and labeling requirements.
  • Develop and refine evaluation scopes and methodologies to ensure project objectives are met efficiently.
  • Create and implement detailed workflows, including annotation guidelines and training materials, to standardize labeling processes.
  • Identify and employ the most effective resources—human annotators, LLMs, or hybrids—for project success.
  • Manage external vendor relations, ensuring quality and efficiency in delivered outcomes.

Must-Have Skills:

  • Proven track record in data labeling or human evaluation program management.
  • Solid understanding of machine learning concepts and applications.
  • Exceptional project management skills, capable of leading multiple projects simultaneously.

Industry Experience:

  • Experience in technology or content-driven environments is preferred, with a particular focus on machine learning applications and human-in-the-loop systems.

Education:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, Statistics, or a related field.

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