Founding Engineer, Open Source

Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right.

We’re at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, chandra, surya, marker, and lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face.

We're looking for a Founding Engineer to develop and evangelize our open source repos. This includes chandra, surya, marker, pdftext, and lift, which collectively have over 70k Github stars. It also includes new tools we have yet to build and launch.

As you work on our repos, you’ll also become the credible person to evangelize them. You’ll turn your own work into demos, benchmarks, tutorials, and launches. You’ll also support other launches across Datalab, especially when they touch open source components like the SDK.

Our projects have real reach: 70k+ GitHub stars and users everywhere from frontier AI labs to Fortune 500s. Your job is to turn that reach into a thriving, engaged developer community through content, code, and showing up where developers already are.

If you're the kind of engineer who’s energized by both building things and helping other people build, this is the role for you.

• Have experience with OCR, document AI, or structured extraction

• Have contributed to or maintained a widely-used open-source ML/vision/NLP project

• Have a growing audience on YouTube, X, or Twitch, or an active presence in developer communities

• Have used (and loved) marker, surya, chandra, or lift

1. 30-minute video call to evaluate fit

2. 1.5-hour in person meeting to build an architecture together

3. Async code sharing + review phase (not a take-home project, you just share some code samples)

4. Culture fit interviews with the team

At this stage of the company, every interview is somewhat custom, so these phases may be rearranged slightly.

Datalab is an equal opportunity employer. We do not discriminate on the basis of any characteristic protected by federal, state, or local law.

If you need an accommodation to participate in our hiring process, or if you believe you have experienced discrimination or harassment at any point in it, contact operations@datalab.to.