About Us
Great prompts, workflows, and agents are being built every day—but there’s no native way to prove who created what, track how it’s used, or ensure creators get paid when their work delivers value.
0em Labs is building a protocol that turns every AI artifact—prompts, RAG pipelines, agent skills, evals, UI snippets—into a composable, credited, and cash-flowing asset.
Think Git + Stripe for AI, built on Web3 rails so both humans and agents can transact without gatekeepers.
Our goal is to enable businesses to spin up, automate, and monetize AI tooling without worrying about attribution or payments. We provide the rails, receipts, and revenue share that make this possible.
Our Team
We’re a tight-knit team of five with deep technical and entrepreneurial experience in AI and Web3.
We've shipped products and led teams at Ripple, Tron, Theoriq, and ElizaOS, and worked directly with partners like the Coinbase Developer Platform, Monad, and Abstract.
If you're excited about building alongside people who move fast, think deeply, and care about the future of AI—you'll fit right in.
What Are Model Context Protocols (MCPs)?
Model Context Protocols (MCPs) are a new open standard that allow AI tools to connect to live data, external services, and APIs—giving them real-time awareness and the ability to act in the world.
At 0em Labs, MCPs are modular, shareable units that define:
* What an AI tool does
* What it can access
* How it gets paid
Examples include:
* A support bot that connects to your CRM
* A research interface that pulls live data from APIs
* A content engine that writes and publishes automatically
The Role: AI Engineering Intern
We’re looking for undergraduate students in Computer Science, Machine Learning, or related fields who are seeking an internship with the potential to grow into a full-time role.
This is a hybrid role between engineering and applied AI research. You’ll help develop AI workflows, experiment with LLMs, and contribute directly to our MCP-based infrastructure.
You’ll:
* Design and prototype AI tools using LLMs and the MCP framework
* Work with prompts, APIs, and agent workflows
* Explore integrations with third-party services and real-time data
* Collaborate with the core engineering team
* Refine tools based on real user feedback
* Contribute to product development, system architecture, and open standards
Who You Are
We’re looking for sharp, curious undergraduate students currently pursuing a degree in Computer Science, Machine Learning, or a related field—who are excited to build real-world AI systems and interested in exploring a full-time role after the internship.
You might be a great fit if you:
* Are currently studying and seeking an internship with the potential to transition into a full-time role
* Have experience working with large language models (e.g., OpenAI, Claude, open-source models)
* Are proficient in Python and API-based development
* Have explored prompt engineering, few-shot learning, or RAG pipelines
* Enjoy building quick prototypes and experimenting with AI tooling
* Think critically about how AI systems are used in production
Bonus if you have:
* Experience with LangChain, AutoGen, or similar frameworks
* Contributed to open-source AI projects
* Knowledge of AI evaluation, safety, or observability techniques
* Familiarity with Web3, smart contracts, or programmable incentives
* Experience designing human-in-the-loop or user-facing AI systems
Why Join 0em?
* Work on cutting-edge AI infrastructure in a startup setting
* Remote-first with flexible, async-friendly collaboration
* Earn equity + future token incentives
* Collaborate with high-caliber engineers, researchers, and founders
* Help define how AI tools are built, shared, and monetized in the future
Location: Remote
Type: Internship (Undergraduate – Computer Science or Machine Learning)
Compensation: Unpaid (with Equity + Token Incentives)
Note: We are currently fundraising. Salary compensation will begin post-raise.
Apply Now
Let’s build the future of work together.
Send your CV to info@0emlabs.org with the subject line: AI Engineering Internship Application, or apply directly via LinkedIn.