AI Content Engineer
LlamaIndex provides AI document-processing and knowledge-agent infrastructure, centered on LlamaParse for parsing, extraction, indexing, and retrieval over unstructured enterprise documents.
About LlamaIndex
A San Francisco AI company offering a developer-first platform and commercial APIs for document workflows and knowledge agents. Its active products include LlamaParse, agentic OCR and structured extraction software, and the open-source local document parser LiteParse.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build and maintain benchmarks for document parsing and understanding, run experiments, and turn findings into technical analyses, reports, tutorials, and comparisons. You will contribute code, notebooks, examples, and documentation while staying current on document AI research and engaging developers through technical content.
Requirements
- Software engineering experience
- Production Python experience
- Knowledge of modern machine learning techniques
- Knowledge of computer vision, NLP, or multimodal learning
- Technical writing
- Research paper analysis
- Document AI
- Vision-language model
- Transformer architecture
- Evaluation framework
- OCR
- Layout analysis
- Table extraction
- Document structure understanding
- LLM application
- RAG
Responsibilities
- Design, build, and maintain benchmarks for document parsing and understanding
- Publish technical content including blog posts, benchmark reports, comparisons, and tutorials
- Research document AI models, papers, competitors, and techniques
- Run experiments and translate findings into publishable artifacts
- Produce technical analyses comparing capabilities with alternatives
- Contribute open-source examples, notebooks, and documentation
- Surface improvements and capabilities through collaboration with the ML team
- Engage the developer community through technical content
Benefits
- Equity