Data Operations Manager, Human Data

Overview

Build and scale data operations across research teams working on frontier AI capabilities, owning the data pipeline from requirements to production and managing vendor relationships.

What you'll do

• 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

What you'll need

• 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
• Familiarity with how LLMs work or strong interest in understanding AI training methodologies
• Highly organized and able to 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
• Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience
• Required field of study: a field relevant to the role as demonstrated through coursework, training, or professional experience

Nice to have

• 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

Details

• Locations: San Francisco, CA or New York City, NY
• Location-based hybrid policy: staff expected in an office at least 25% of the time, though some roles may require more
• Visa sponsorship available, though not guaranteed for every role and candidate
• Annual salary: $270,000 to $365,000 USD