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David Careers

Founding Engineer (Data, ML, Product) Intern

Posted yesterday

anonymousBrooklyn (NY)
Computer Systems Engineers/ArchitectsSoftware Publishers

SENIORITY

Intern

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About the role

The company We are a stealth stage startup building data infrastructure for a large, underserved financial vertical. We take public records that today are slow, fragmented, and hard to trust, and turn them into a fast, reliable decision product that professionals will pay for. The company is a Delaware C corp, funded by founder capital, raising a pre seed round in 2026. The full thesis, market, and product are shared under NDA once we are in conversation.
The role: You are the support of the first engineer. You, the CTO are the entire engineering team through pre seed. This is not a narrow role. You own systems end to end: data ingestion, the data model, the ML that powers the core product, and the product surface a customer touches. If you want a defined box, this is the wrong job. If you want to build a real system from the first commit and watch customers use it within months, this is the right one.
What you will do:
  • Build and operate the data pipelines that pull large volumes of public data into a clean, queryable store.
  • Design the data model that turns raw records into trustworthy entities other systems depend on.
  • Build the ML layer that links and scores records at scale, with measurable accuracy.
  • Ship the serving API and the first product surface customers use.
  • Set the engineering patterns the company builds on for years.
  • Work runs in two week cycles. Something real ships every cycle.
  • What we look for1-2 plus years building production systems, with real depth in data engineering, ML, or both.
  • You have built and run data pipelines other people depend on.
  • You can carry a problem from messy source data to a working product feature with no one architecting it for you.
  • You write code that holds up, and you make sound calls under ambiguity.
  • You want the responsibility of being early, not the comfort of a defined box.
  • Strong pluses
  • Record linkage, entity resolution, or graph data experience.
  • Background in fintech, credit, real estate, or public records data.
  • You have been an early engineer or founder at a startup before.
  • StackData: Python, dlt for ingestion, SQLMesh for transforms, DuckDB and DuckLake on S3 as the lakehouse.
  • Orchestration: Dagster.
ML: Splink and Python for record linkage and scoring. Backend: FastAPI, Postgres, Clerk for auth. Frontend: Next.js and TypeScript. Infra: Pulumi for infrastructure as code, AWS.Tooling: Codex and Claude Code used heavily; a small team shipping like a large one is the point. You do not need every tool on this list. You do need to be the kind of engineer who picks one up fast.
Compensation: This is an unpaid intern role - stock based compensation is something that will be considered based on revenue hurdles following the public launch of the product.
Logistics: New York City, in person, full time. Reports to the CTO.
How to apply: Send a short note and one thing that shows how you think and build: a project, a system you are proud of, or code. We share the full company thesis under NDA early in the process.

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