About Datalab

Datalab is an applied research lab in New York. We train our own models to turn documents into data you can verify: scans, dense tables, handwriting, the pages other tools quietly get wrong.

Because we own the models, a customer's hard problem becomes a roadmap conversation, not a feature request. Our open-source work (Marker, Surya, Chandra) has more than 75,000 GitHub stars. Customers include Anthropic, ElevenLabs, Gamma, Reflection AI, and Legora, along with insurers, financial firms, and healthcare companies. We deploy anywhere from our API to fully air-gapped on-prem.

We're a small, founder-led team. You'll have real influence on how we sell and what we build.

Role Overview

Marketing at Datalab already has real infrastructure. We run a combined launch and content calendar with a defined playbook - channels, owners, and cadence for every release - and we ship two to three launches a week against it. No one here works on marketing full-time, so nobody owns the bigger question of how we show up when a developer, a buyer, or an AI agent looks for a document parser.

You’d be our first dedicated marketing hire. You’d inherit a working system rather than a blank page, and your job would be to run it reliably, then make it considerably more ambitious. The natural place to build from is our open source work, which reaches a wide audience and currently does less for us than it could.

This is a hands-on role. On a team of 15, you’ll write the blog post, draft the tweets, restructure the docs page, brief the agency if we hire one, and pull the numbers yourself. We’re looking for someone who's done this work well somewhere and wants to keep doing it, rather than direct someone else who does.

This role has strong potential to grow into a leadership role as we hire more people into the marketing team.

An increasing share of our buyers never touch a search results page; they ask a model. We want someone who takes seriously how Datalab gets recommended by LLMs and agents, how our site, docs, and benchmarks are structured, where models pull their answers from, and how we measure it all. Nobody has fully figured this out yet, and we’d like you to be the person who figures it out.

If you want to inherit a brand book, a content team, and a defined category, this isn’t the right role. If you want to shape how a technical category gets talked about, with real customers and real distribution to work from, it’s a good one.

Day to day you will

A typical week might look like: shipping the launch post for a new open source model, ghostwriting a thread for one of our researchers, editing a vertical explainer on tracked-changes extraction for legal teams, restructuring a docs page so a model can actually cite it, answering a sharp question in Discord, and digging into why organic signups dipped last week.

Own our model launches, especially open source. Every release - Chandra, Surya, Marker, Lift, and what comes next - should land. You’ll build the assets (launch posts, benchmark write-ups, demos, docs), coordinate the team’s posts, work HN and Reddit and the ML community, handle press where it’s worth handling, and run the retro afterward so the next one lands harder.

Take over and scale the content engine. Inherit the calendar, tighten the cadence, and own the strategy and much of the writing. Educational content for developers evaluating us, and vertical-specific content for the buyers who need to see their own documents in the example - legal, healthcare, financial services, insurance, logistics, government.

Ghostwrite for the team. Our engineers and researchers know things worth writing about and mostly won’t write it themselves. You’ll draft in their voice, in a way they’re glad to put their name on, and turn the team into a distribution channel.

Make Datalab legible to LLMs and agents. Structure the site, docs, and benchmark content so that models recommend us when someone asks how to parse a PDF. Own the technical work behind it, figure out what “ranking” even means in this context, and build a way to measure whether it’s working.