MLabs is a rapidly growing AI company that helps AI teams ingest real-world enterprise data with state-of-the-art accuracy. Their platform trains vision models and integrates LLMs to read unstructured documents, enabling customers to build products and automate processes at scale. They are seeking a Backend/AI Engineer to work on their core document processing API to build and optimize the core infrastructure that makes state-of-the-art document understanding accessible at scale.
Requirements
- 2+ years of experience building real-world applications and integrating LLMs into production systems.
- Exceptional proficiency in Python.
- Experience with prompt engineering, fine-tuning, or building AI agents.
- Keeps up with the latest developments in ML/AI.
Responsibilities
- Integrating and optimizing LLM calls for structured extraction, form filling, and complex document understanding tasks.
- Building and improving document processing pipelines that handle everything from PDFs to spreadsheets at scale, based on vision models and LLMs.
- Making improvements to API design and pre-processing algorithms (chunking, structured extraction, etc.) based on critical customer feedback.
- Experimenting with new techniques and output structures to improve LLM accuracy and reduce latency.
- Building internal tooling and evals to better understand and analyze failure cases.
- Working directly with the founders and customers to shape the product direction and engineering strategy.
Other
- 1-5 years overall experience, ideally in a startup/0-to-1 setting.
- A quantitative approach to building products, with the ability to debug, experiment, and iterate fast.
- High bar for quality; you ship fast with high agency and actively jump in to fix problems (not settling for 90%).
- Prior experience founding a company or building products at early stages.
- 100% On-site in San Francisco, CA. The role requires working hard and moving quickly.
