Job Title:Data Ops Manager with AI/ML exp

Location:Mountain View, CA

Duration: 12 months 

Bill Rate: $79/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

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 10+ 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