Vendra (vendra.io) is the AI native marketplace transforming how the world’s most advanced teams source custom parts.

Our customers are building the future. Robotics companies, defense contractors, and deeptech unicorns pushing the limits of manufacturing and autonomy. From Apple to Skydio to NASA, these teams used to spend weeks searching for suppliers, calling to check bandwidth, and waiting even longer for quotes on mission critical parts, often with entire procurement teams buried in spreadsheets and email chains.

Now they use Vendra.

They submit one RFQ. Our AI agents instantly activate sourcing workflows that tap into our network of manufacturers, contact suppliers directly, pull real time data on pricing, capacity, and lead times, and return fully verified build paths tailored to their exact spec. No middlemen. No bottlenecks. Just answers.

They use us to get the parts they need to build. It is that simple.

About Vendra ⚙️

We’re building an AI-native manufacturing marketplace transforming how the best companies get custom parts manufactured. There aren’t many early stage companies where you’ll get to work with industry titans like Apple and Anduril, solving their hair on fire problems, but you will at Vendra.

We help teams at these companies (and many more) get their critical hardware built in the United States through smarter supplier matching and automation. Our vision is to become the only platform that an engineer ever turns to when they need things made. 

We’re backed by Y Combinator and top investors, and we’re building a team to ship fast and solve hard problems as we continue to build and scale.

Note: Vendra is ITAR registered and works on federal and defense programs. All employees must be US citizens located in the US. 

About the founders 👨‍🔧👨‍💻

• Anish (CTO) built machine learning algorithms for one of the largest satellite datasets in the world at General Atomics, and was founding machine learning engineer at Ship Angel
• Shan (CEO) worked on next-gen hardware at Microsoft (HoloLens 2), Apple (Vision Pro), and designed most of the cameras on Skydio’s latest generation X10 drone, spending months working onsite with manufacturers across the US and Asia

About the Role 👨‍🚀

As a Full Stack ML Engineer Intern, you’ll help us build the ML and AI infrastructure behind our quoting engine, vendor selection models, and internal tooling. You’ll work closely with our founders and high impact team to bring data and models into production. This will be a 3-6 month internship, and may be converted to a full time position at the end of the internship.

What You’ll Do

• Build and maintain data pipelines for supplier intelligence, RFQ data, and quoting behavior
• Collaborate on training and serving models for pricing, matching, and insight extraction
• Integrate ML models with user-facing product features (React + Python + API layers)
• Build tools for model evaluation, prompt tuning, and observability
• Contribute to AI-agent workflows using retrieval, embedding search, and structured chaining

What We’re Looking For

• Prior experience building ML-driven applications through internships (research or corporate), startups, or advanced coursework
• Strong foundation in Python and ML frameworks (scikit-learn, PyTorch, etc.)
• Familiarity with full-stack workflows frontend (React), backend (FastAPI), deployment (AWS)
• Bonus: Experience with VespaDB, LangChain, and/or RAG architectures
• Bonus: Familiarity with tools like Cursor and Claude Code
• Super Bonus: Experience building physical things (hardware design, testing, validation, etc.)

If you’re somebody who loves solving open ended problems and building software to shape the physical world, Vendra is the place for you.

Our AI agents operate like autonomous sourcing analysts. They ingest RFQs, query global manufacturers, analyze quote data, and return verified build paths in minutes. We work closely with customers building advanced robotics, aerospace, and defense systems. Speed, reliability, and accuracy are mission critical.

We care about clean system architecture, performance under pressure, and fast iteration. Everyone ships.

Tech stack:

• Frontend: React, TypeScript
• Backend: Node.js, Python
• ML and Agents: OpenAI, Claude, fine tuned models, custom LLM orchestration
• Infra: AWS, Postgres, Redis, S3, Vercel, Docker
• Data: Real time quote intelligence, supplier availability, historical manufacturing performance

We are looking for engineers who want to move fast, own real product surfaces, and help define how custom parts are sourced in the future.