Ethereum Foundation
AI

Member of AI Staff

Ethereum Foundation · San Francisco · $64k - $86k

Actively hiring Posted 6 months ago
About the Ethereum Foundation

The Ethereum Foundation (EF) is a global non-profit dedicated to supporting Ethereum’s long-term success. Our mission is to allocate resources to critical projects, advocate for Ethereum within the ecosystem, and promote its vision to the world.

About the Team and Role

The EF recently launched the dAI Team, focused on making Ethereum the global, decentralized settlement and coordination layer for AI. Our aim is to pioneer the field of AI on blockchains: defining standards, supporting open-source builders, and laying the groundwork for AI systems that are secure, verifiable, and censorship-resistant.

As a Member of AI Staff, you will join a small, research-driven group tackling frontier problems at the intersection of AI and decentralized systems. You’ll work on open questions around multi-agent coordination, verifiable inference, privacy-preserving compute, and decentralized infrastructure for AI. The role is highly collaborative, spanning research, engineering, and engagement with leading AI and Web3 projects worldwide.

Key Responsibilities

Lay the foundations of a new discipline (AI on blockchains): Conduct foundational research at the intersection of AI and Ethereum—multi-agent systems coordination, decentralization of key components in the AI stack, AI system validation, and privacy.

Close the chasm between Ethereum and AI communities: Forge relationships and collaborations with AI researchers and practitioners—both industry and academic—through co-writing ERCs/EIPs (such as ERC-8004 which is getting a lot of traction in the ecosystem), contributing to open source AI projects and frameworks, co-authoring papers, and presenting at major conferences.

Influence the roadmap of the dAI Team: Translate research into applied proposals that improve the Ethereum protocol and ecosystem infrastructure.

Research in conversation with the community, not in isolation: AI on Ethereum is fundamentally about using the chain as a coordination layer to foster security, privacy, composability, and other properties that centralized AI cannot provide. Staying closely connected to the community is a priority—both by actively sharing new projects and results outwardly, and by drawing inspiration from the many experiments ecosystem teams are running in this emerging field.

Requirements

Relevant background: Demonstrated skills related to state-of-the-art model development practices, emergent frameworks and tooling, or privacy-preserving compute methods. Prior experience with blockchain protocols is a plus. Contributions to open source AI or distributed systems projects are especially valued.

Research excellence: Strong background in research, whether in academia, labs, or applied industry settings. Experience ideally includes AI, distributed systems, optimization, or cryptography. A PhD is welcome but not required if you have a strong track record of impactful projects.

Excellent communication and collaboration skills: Comfortable collaborating with diverse teams across both the AI and open-source/blockchain ecosystems, as well as with academic researchers and industry practitioners.

Passion for decentralized AI: Strong motivation to carve an alternative path for AI—one that is open source, censorship resistant, democratic, private, and secure.

Ability to thrive in a distributed environment: Comfortable working in a fully remote, asynchronous organization across time zones.
How We Work

We work like an open applied research lab embedded in the Ethereum ecosystem. Most contributions are public by default, and we collaborate directly with academics, independent researchers, startups, and open-source communities. The culture rewards initiative, rigorous thinking, and a willingness to engage across disciplines. This role is ideal for someone who wants to shape the foundations of a new field, while staying close to both research and real-world applications.

Other Details

This is a full-time role. Our team is distributed globally and remote work from anywhere is possible—with most synchronous time from 2pm UTC onwards.

Some travel to events (Devcon, Devconnect, AI × Ethereum workshops) is expected.

Competitive compensation, flexible time-off.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Tags & focus areas

Used for matching and alerts on DevFound
Ai Blockchain Ethereum
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.