Data Operations Manager, Human Data

Anthropic•San Francisco, CA

20h•$270,000 - $365,000•Hybrid

About The Position

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The Data Operations Manager will build and scale data operations across research teams working on frontier AI capabilities. This role involves partnering with researchers to design and execute data strategies, managing vendor relationships, and owning the entire data pipeline from requirements to production. The position requires operational excellence and technical depth to understand high-quality training data, with a focus on strategy and execution. The data operations built will directly impact model performance on critical capabilities such as tool use accuracy, prompt injection robustness, long-horizon reasoning, and safety alignment. The role is for someone excited about scaling quality across diverse research areas, understanding technical requirements, building partnerships, and executing flawlessly, thriving at the intersection of operational excellence and cutting-edge AI research.

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

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

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