Head of Research

Avra · Remote

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About Avra

Foundation models learned to read text, images, and code. The data that runs the economy hasn't had its moment yet. It's structured: customers, accounts, transactions, and claims, stored in relational databases, connected as graphs, and moving through time. Every credit approval, fraud block, and retention offer is a prediction over that data. Today each one is still a bespoke model, rebuilt by hand for every task, schema, and company.

We're building foundation models for structured data, such as relational databases, graphs, and time series. Take a relational database: one pretrained model should read any company's database, understand its schema from the names of its tables and columns, and adapt to a new prediction task without a feature-engineering project or a model trained from scratch.

Avra exists to build those models and the platform that turns their predictions into decisions running in production, in our cloud or inside an enterprise's own infrastructure. We're an AI research lab with our home in São Paulo, backed by Sequoia and Andreessen Horowitz, and we ship with enterprise design partners in banking, payments, telecom, and commerce, including Mercado Livre, Inter, PicPay, Banco BV, and Vivo.

About the team

We are a small group of researchers, engineers, and company builders, with our home in São Paulo and a team spread across San Francisco, Latin America, and Europe. Research is one team working on one portfolio: pretraining, post-training, data, and evaluation for our foundation models. Research leadership is shared between two peers. Our Chief Scientist owns scientific direction and the standard of evidence. The Head of Research owns whether the team delivers.

Our researchers have published widely at venues like NeurIPS and ICLR. You can find our work on our research page.

Your mission

Make Avra's relational foundation model the best in the world, and build the team that keeps it there.

What you'll own

You'll stay hands-on: reading code, running experiments, and going into the details of a training curve when something looks wrong.

What we hope you'll bring

Bonus points if you have

How we interview

  1. Intro call with the CTO (45 min). Your path, and what you'd want this role to be.

  2. Deep dive (60 min). A team or research program you led: the bets, the results, and the calls you'd make differently.

  3. Portfolio exercise (90 min). We share context on where the model is today. You come back with a written plan for the next two quarters and walk the CTO and Chief Scientist through it.

  4. Research team (60 min). A session with the researchers you'd lead, without the founders in the room.

  5. Founders (45 min).

  6. References.

Logistics

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