Lead, Data Campaigns for AI Personalization

River AI Inc.; Palo Alto (CA); On-site; USD 200,000 - 300,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

Unlimited PTO

Relocation assistance

Job summary

River AI Inc. is seeking a data campaigns lead to design and run campaigns and evaluations for next‑generation models and personalization systems.

You will work with research and product teams to determine data needs and build training recipes and interfaces for tutors and users. You will oversee partnerships with data labelers, manage scalable data operations, and drive continual learning initiatives to improve model personalization.

Qualifications

• Completed or in-progress bachelor's degree or higher, or equivalent professional experience.
• Extensive experience running large-scale data campaigns at frontier AI company or research institution.
• Exceptional oral and written communication skills.
• Operational experience hiring or managing human data labelers.
• Evidence of expertise in a non-technical domain (e.g., literature, philosophy, history, economics, sociology, psychology, political science).
• A highly collaborative mindset and a bias for action in a fast-paced environment.

Responsibilities

• Build and oversee data campaigns feeding training pipelines for next-generation agents and personalization systems.
• Create evaluations for general capabilities, model behavior, continual learning, personalization.
• Architect and deploy new clients and interfaces for collecting feedback from tutors and users, in collaboration with product and research teams.
• Manage external partnerships with data labelers on various campaigns.

Skills

Data campaigns

Data labeling

Communication skills

Hiring data labelers

Non-technical expertise

Collaboration

Education

Bachelor's degree

Tools

LLM systems

Job description

River AI Inc. is seeking a data campaigns lead to design and run campaigns and evaluations for next‑generation models and personalization systems.

You will work with research and product teams to determine data needs and build training recipes and interfaces for tutors and users. You will oversee partnerships with data labelers, manage scalable data operations, and drive continual learning initiatives to improve model personalization.