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Research Scientist (AI Agent Economies)

Research Scientist (AI Agent Economies) | naptha.ai

About this role

We are seeking an exceptional Agent Economics Researcher to study and design incentive structures and economic systems for large-scale AI agent networks. This is a rare opportunity to shape the future of AI agent infrastructure at a massively ambitious scale, backed by industry veterans and technical leaders through NVIDIA Inception, Google for Startups, and Microsoft for Startups.

We're building the foundational infrastructure for the next wave of AI companies, enabling frontier AI developers (many leaving labs like OpenAI, Anthropic, and DeepMind) to build products powered by enormous networks of highly capable next-generation AI agents. As our Agent Economics Researcher, you'll develop the theoretical and practical frameworks for how agents cooperate, compete, and create value within complex networks.

Core Responsibilities

  • Design and study economic mechanisms for agent networks

  • Research incentive structures for agent collaboration

  • Develop frameworks for resource allocation and optimization

  • Study economic behavior patterns in agent systems

  • Create models for agent value creation and exchange

  • Research market dynamics in agent networks

  • Design experiments to validate economic theories

Research Areas

  • Mechanism design for agent systems

  • Game theory in multi-agent networks

  • Resource allocation optimization

  • Market design for agent economies

  • Incentive alignment in agent networks

  • Economic efficiency in distributed systems

  • Value creation and capture in agent networks

You're a good fit if you have:

  • PhD or equivalent experience in Economics, Computer Science, or related field

  • Strong background in mechanism design and game theory

  • Experience with multi-agent systems or markets

  • Understanding of distributed systems economics

  • Strong mathematical and analytical skills

  • Interest in both theoretical and applied research

  • Ability to translate economic theory into practical systems

Required Experience:

  • Research experience in economics or mechanism design

  • Strong mathematical and modeling skills

  • Programming ability for economic simulations

  • Track record of novel research contributions

  • Understanding of distributed systems

  • Experience with experimental design

About the hiring process:

  • Research presentation

  • Economic design challenge

  • Technical discussion

  • Team collaboration interview

  • Vision and strategy workshop

Compensation & Benefits:

  • Highly competitive salary and significant equity stake

  • Remote-first work environment

  • Full medical, dental, and vision coverage

  • Flexible PTO policy

  • Research conference budget

  • Publication support

  • Learning and development budget

Additional Notes:

  • Must be comfortable with ambiguity and rapid iteration typical of pre-seed startups

  • Strong bias for practical implementation of research ideas

  • Passion for advancing the field of multi-agent systems

  • Interest in open source contribution and community engagement

This is a unique opportunity to shape the economic foundations of future AI systems, designing the mechanisms and incentives that will govern how agents interact and create value at scale.

Average salary estimate

$135000 / YEARLY (est.)
min
max
$120000K
$150000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Research Scientist (AI Agent Economies), Naptha AI

Are you ready to dive into the cutting-edge world of AI and make a difference? Naptha.AI is looking for a Research Scientist (AI Agent Economies) to join our dynamic team in San Francisco. In this role, you'll have the unique opportunity to study and design the economic structures driving large-scale AI agent networks. Imagine shaping the future of AI infrastructure alongside industry veterans and technical leaders from giants like NVIDIA, Google, and Microsoft! As our Research Scientist, you'll be developing the frameworks that allow AI agents to cooperate, compete, and create real value within complex systems. This position calls for an innovative thinker with a solid background in economics, mechanism design, and game theory. Your work will involve designing economic mechanisms, researching incentive structures, and studying behavior patterns in agent systems. You'll even get to conduct experiments to validate your theories! If you've got a PhD or equivalent experience, strong analytical skills, and a passion for applied research, this is your chance to make your mark in the AI landscape. Plus, you'll love our remote-first culture, competitive salary, and flexibility that allows you to thrive. Together, let’s build the next wave of AI-powered solutions!

Frequently Asked Questions (FAQs) for Research Scientist (AI Agent Economies) Role at Naptha AI
What are the core responsibilities of a Research Scientist (AI Agent Economies) at Naptha.AI?

As a Research Scientist (AI Agent Economies) at Naptha.AI, your core responsibilities will include designing and studying economic mechanisms for agent networks, researching incentive structures for collaboration, developing frameworks for resource allocation, and analyzing economic behaviors within these systems. You'll also be involved in creating models for agent value creation, studying market dynamics, and conducting experiments to validate various economic theories.

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What qualifications do I need to apply for the Research Scientist position at Naptha.AI?

To apply for the Research Scientist (AI Agent Economies) role at Naptha.AI, candidates are expected to hold a PhD or equivalent experience in Economics, Computer Science, or a related field. A strong background in mechanism design and game theory is essential, along with experience in multi-agent systems or markets. Candidates should also demonstrate strong mathematical and analytical skills, an ability to apply theoretical research practically, and proficiency in programming for economic simulations.

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What is the hiring process for a Research Scientist (AI Agent Economies) at Naptha.AI?

The hiring process for the Research Scientist (AI Agent Economies) position at Naptha.AI involves several stages: a research presentation, an economic design challenge, a technical discussion, a team collaboration interview, and a vision and strategy workshop. Each of these steps is designed to assess your skills, creativity, and fit within our innovative team.

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Can you describe the work culture at Naptha.AI?

Naptha.AI embraces a remote-first work environment that fosters flexibility and collaboration. Our team values practical implementation and embraces the ambiguity often found in pre-seed startups. You'll find that we encourage community engagement and open-source contribution while providing ample opportunities for learning, development, and research publication support.

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What kind of projects can I expect to work on as a Research Scientist (AI Agent Economies) at Naptha.AI?

As a Research Scientist (AI Agent Economies) at Naptha.AI, you can expect to work on pioneering projects that involve designing incentive structures for agent collaboration, developing resource allocation frameworks, and studying market dynamics in agent networks. You'll be engaged in innovative research on mechanism design, game theory applications, and economic efficiency in distributed systems, contributing to foundational knowledge in AI agent infrastructure.

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Common Interview Questions for Research Scientist (AI Agent Economies)
What motivates you to work in AI agent economies?

When answering this question, highlight your passion for AI and its potential to transform economies. Discuss how the intersection of economics and technology excites you, and provide examples of projects or research that align with your motivations.

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How do you approach designing economic models for agent systems?

In your response, detail your process for designing economic models, including your reliance on mathematical frameworks, real-world data, and simulations. Be sure to mention your experience with mechanism design and how you validate your models through experiments.

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Can you explain a complex economic concept related to multi-agent systems?

Choose a complex economic concept such as game theory or incentive alignment, and be prepared to explain it in simple terms. Use real-world analogies if possible, and reflect on how this concept applies to your previous research or how it can be implemented in agent systems.

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What strategies do you employ to validate your economic theories?

Discuss the importance of empirical validation in your work. Describe the methodologies you use, including simulations, experiments, and collecting data, and give a brief overview of a successful validation project you've completed.

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How do you ensure collaboration among AI agents in your models?

Talk about your approach to designing incentive structures that facilitate cooperation among agents. Highlight the role of reward mechanisms and resource sharing in fostering collaboration, and mention any relevant techniques or frameworks you have employed.

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What challenges have you faced in mechanism design, and how did you overcome them?

Reflect on specific challenges you've encountered in mechanism design, such as achieving fairness or efficiency. Discuss the strategies you adopted to address these challenges and share what you learned that could be beneficial in future projects.

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Describe your experience with multi-agent systems.

Focus on your practical experience with multi-agent systems, explaining any projects or research you’ve conducted. Discuss the frameworks you used and the outcomes, emphasizing your ability to blend theoretical concepts with practical implementations.

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Why do you believe incentive structures are crucial in AI agent economies?

Articulate your belief in the critical role of incentive structures in ensuring that agents act in ways that are beneficial to the system as a whole. Provide examples of how well-designed incentives can lead to better outcomes and efficiency in agent interactions.

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How do you keep updated with the latest research in economics and AI?

Share your strategies for staying informed about current research and trends, such as attending conferences, reading relevant journals, and engaging with the academic community. Emphasize your commitment to lifelong learning and adaptation.

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What are your long-term goals as a Research Scientist in AI?

Outline your aspirations within the field of AI, discussing any specific areas of research you hope to explore further. Explain how your goals align with the mission of Naptha.AI and how you envision contributing to the company's future.

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Full-time, remote
DATE POSTED
November 30, 2024

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