Member of Program Staff, Data

At River, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, bespoke training infrastructure, next-generation UIs, and frontier deep learning research.

About the Role

We are looking for exceptional people to oversee our data efforts. Your main goal is to design and run data campaigns and evaluations for next-generation models and personalization systems. You will also play a significant role in crafting our training recipes and interfaces for tutors & users.

What You’ll Do

• Build & oversee the data campaigns that feed training pipelines for next-generation agents and personalization systems. You will work closely with our research teams to figure out what data is needed.
• Create evaluations for general capabilities, model behavior, continual learning, personalization.
• Architect and deploy new clients & interfaces for collecting feedback from tutors and users, working closely with both product and research team members.
• Manage external partnerships with data labelers on a variety of campaigns.

Skills & Qualifications

Minimum Qualifications:

• Completed or in-progress Bachelors or higher degree, or equivalent professional experience.
• Extensive experience running large-scale data campaigns or post-training at frontier AI company or research institution.
• Exceptional oral and written communication skills.
• Operational experience with hiring or managing human data labelers.
• Evidence of expertise / top of field in a non-technical domain, such as but not limited to: literature, philosophy, history, economics, sociology, psychology, political science.
• A highly collaborative mindset and a bias for action to push boundaries in a fast-paced environment.

• BA, Masters, or Ph.D. in a humanities, social science, or STEM.
• Experience with managing external partnerships and contracts.
• Exceptional product judgment with the ability to reason backward from user needs, alongside a high degree of ownership to navigate ambiguity.
• Hands-on experience with LLM systems, including APIs, agents, tool calling, prompt iteration, eval frameworks, and inference constraints.
• Familiarity with modern deep learning algorithms including reinforcement learning, supervised fine-tuning.

Logistics & Benefits

• Location: Palo Alto, California.
• Compensation: Depending on experience and skills the expected base pay is $200,000 - $300,000 USD per year, plus equity.
• Benefits: Comprehensive health, dental, and vision insurance; unlimited PTO; and relocation assistance as needed.
• Visa Sponsorship: We sponsor visas and are committed to supporting the process for the right candidate.