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AnthropicAnthropicSan Francisco, CA

Data Operations Manager, Human Data

Data Operations Manager responsible for building and scaling data strategies, vendor partnerships, and high-quality data pipelines to advance frontier AI research in RLHF, safety, tool use, and agentic systems at Anthropic. Requires 3+ years operations/PM experience, strong project management, data analysis skills, and passion for AI safety.

270k – 365k
Hybrid3+ YOEData Engineering

About the role

Responsibilities

  • Own and execute data strategy for research teams advancing frontier AI capabilities across RLHF, safety, tool use, and agentic workflows
  • Drive strategic vendor partnerships and build scalable frameworks for technical data collection at scale
  • Design and implement operational systems that translate research requirements into high-quality data pipelines
  • Build evaluation frameworks and quality standards that ensure data meets the bar for training state-of-the-art AI systems
  • Lead cross-functional initiatives to optimize research velocity while maintaining rigorous quality standards
  • Proactively identify risks, bottlenecks, and opportunities to improve efficiency and effectiveness across data operations
  • Partner with senior research leaders to align data operations with model development roadmaps and strategic priorities

Requirements

  • 3+ years in operations, consulting, product management, or program management roles
  • Exceptional project management skills with ability to handle multiple complex projects simultaneously
  • Strong communication skills and can engage effectively with technical and non-technical stakeholders
  • Familiar with how LLMs work or have strong interest in understanding AI training methodologies
  • Highly organized and can navigate ambiguity effectively
  • Experience with data analysis tools (SQL, Python, Tableau, spreadsheets, or similar)
  • Thrive in fast-paced research environments with shifting priorities
  • Passionate about AI safety and understand the critical importance of high-quality data
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience in a relevant field

Nice-to-Haves

  • Experience with data collection, labeling, or annotation operations for AI/ML systems
  • Knowledge of RLHF, constitutional AI, or human-in-the-loop workflows
  • Background working with research teams at AI companies or research-oriented organizations
  • Experience managing vendor relationships or external contractors
  • Consulting background with experience translating complex requirements into deliverables
  • Track record of implementing process improvements or quality control systems at scale

Skills

Data StrategyVendor ManagementProject ManagementSQLPythonTableauRLHFLlm TrainingData QualityData PipelinesAi Safety

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