AI Content Engineer

LlamaIndex

$135K — $160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in software engineering, preferably with ML engineering or research
  • Strong expertise in production Python development
  • Familiarity with modern machine learning techniques, especially in document AI, computer vision, and NLP
  • Proven ability to write technical content clearly and rapidly
  • Proactive approach to content publication, focusing on fast output
  • Ability to quickly interpret and summarize research papers
  • Self-motivated with a track record of identifying valuable topics for writing

Responsibilities

  • Design, build, and maintain benchmarks for document AI capabilities
  • Publish technical content regularly, including blog posts and benchmark reports
  • Keep updated on advancements in the document AI field
  • Conduct experiments and quickly translate outcomes into publishable materials
  • Create technical analyses comparing performance with competitors
  • Contribute to open-source projects and documentation
  • Collaborate with the ML team to highlight innovations in content
  • Engage directly with developers through technical writing rather than traditional outreach

Benefits

  • Influence how developers perceive document understanding through your work
  • Engage with advanced document AI technology impacting millions of documents
  • Enjoy a high degree of autonomy in content creation and topic selection
  • Play a crucial role in establishing and scaling the technical writing function
Full Job Description
About the Role

We are seeking a highly technical ML engineer who can produce compelling, authentic technical content at high velocity. You will combine deep expertise in document AI with strong writing skills to build benchmarks, publish technical analyses, and establish our position as the definitive leader in document understanding.

This is not a traditional DevRel or Marketing role. You will write real code, build real benchmarks, and run real experiments - then translate that work into published content at a pace far faster than academic publishing. Your output will directly drive awareness and adoption among the developers building the next generation of document-powered applications.

Responsibilities
  • Design, build, and maintain comprehensive benchmarks for document parsing and understanding
  • Publish high-quality technical content at a weekly cadence (blog posts, benchmark reports, technical comparisons, tutorials)
  • Stay deeply current with the document AI landscape - new models, papers, competitors, techniques
  • Run experiments and translate findings into publishable artifacts quickly
  • Produce technical analyses that demonstrate our capabilities against alternatives
  • Contribute to open-source examples, notebooks, and documentation
  • Collaborate with the core ML team to surface improvements and capabilities worth highlighting
  • Engage authentically with the developer community through technical content (not conferences/events)
Required Qualifications
  • Experience in software engineering (ML engineering + research a bonus)
  • Strong software engineering fundamentals with production Python experience
  • Understanding of modern ML techniques, particularly in computer vision, NLP, or multimodal learning
  • Demonstrated ability to write clearly, quickly, and authentically about technical topics
  • Bias toward shipping - comfortable publishing at blog pace, not paper pace
  • Ability to read, understand, and synthesize research papers rapidly
  • Scrappy and self-directed - can identify what's worth writing about and execute end-to-end
  • Track record of high-velocity output in fast-paced environments
Preferred Qualifications
  • Experience with vision-language models, transformer architectures, or document AI specifically
  • Existing portfolio of technical writing (blog posts, tutorials, technical documentation)
  • Experience building evaluation frameworks or benchmarks
  • Familiarity with OCR, layout analysis, table extraction, or document structure understanding
  • Active presence in ML/AI technical communities
  • Experience with LLM applications and RAG systems
Location

In-person in San Francisco.

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