Senior Software Engineering - Machine Learning

225k - $300k | Equity: 0.15% - 0.35% | In-Person: NYC

Datalab trains models that read documents reliably at scale. 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.

Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. We're backed by founding members of OpenAI, FAIR, and Hugging Face.

We’re looking for a fullstack engineer who wants to build the interfaces, tools, and infrastructure that help developers and enterprises use our models. You’ll work across the stack to shape how people interact with OCR, extraction, and document-understanding systems. That includes building core inference workflows, creating intuitive UI for complex parsing tasks, and improving the developer experience across our open-source repos and API.

This is a high-ownership role that blends engineering, product thinking, and community engagement. You will work closely with the founders and the rest of the team to ship features, improve performance, and make our technology accessible to a global community of builders.

You should enjoy working across backend, frontend, performance, and user-facing surfaces. Ship features to our open source repos, API, and internal tooling.

Design and build frontend features that make document parsing more interactive and understandable.

Optimize inference performance and improve the reliability of our frameworks.

Engage with the community on Github and Discord by collecting feedback, debugging issues, and identifying opportunities for improvement.

Support customer implementations with technical guidance and troubleshooting when needed.

You thrive at the intersection of engineering, product, and user experience. 5+ years of fullstack development experience building APIs and/or developer-focused products.

Experience building in early-stage startup environments.

Shipped and maintained production systems serving high-volume traffic.

Experience building with LLMs and agentic workflows.

Bonus points:

Experience with Python ML frameworks (PyTorch, Transformers, etc.) or interest in training models.

Familiarity with document processing, computer vision, or OCR systems.

Maintained or contributed to open-source projects with active communities

Experience writing technical content or demos to showcase your work.

30-minute video call to evaluate fit

J-18808-Ljbffr Data Lab