Data Ops Manager

Role: Data Ops Manager

Location: Mountain View CA - Onsite

Data Ops Manager for QA AI OPS track - 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

You may be a good fit if you:

• Have 3+ years in operations, consulting, product management, or program management roles

• Have exceptional project management skills with ability to handle multiple complex projects simultaneously

• Have strong communication skills and can engage effectively with technical and non-technical stakeholders

• Are familiar with how LLMs work or have strong interest in understanding AI training methodologies

• Are highly organized and can navigate ambiguity effectively

• Have experience with data analysis tools (SQL, Python, Tableau, spreadsheets, or similar)

• Thrive in fast-paced research environments with shifting priorities

• Are passionate about AI safety and understand the critical importance of high-quality data

Strong candidates may also 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