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LlamaIndex

Connects data to large language models

Member of Technical Staff - Applied Research

Computer VisionConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$180k - $250k /yrHybrid

About the Job

Requirements

  • 3–7 years of experience in machine learning engineering, applied research, or research engineering.
  • A strong machine learning foundation, including hands-on experience benchmarking and training models.
  • Strong Python skills and comfort with modern machine learning tooling, especially PyTorch.
  • Experience with computer vision, vision-language models, natural language processing, document AI, optical character recognition, extraction, or agentic AI systems.
  • Ability to build experiments, evaluate results, and iterate quickly toward measurable performance improvements.
  • Strong engineering judgment and ability to write clean, production-quality code.
  • Comfort working in a fast-paced startup environment with high ownership and limited structure.
  • Ability to work adaptably, resourcefully, and self-directedly without waiting to be told what to do.
  • Strong technical writing and communication skills.

Responsibilities

  • Develop and train vision-language models for document processing and document understanding.
  • Build data pipelines for data curation, synthetic data generation, labeling, and benchmark creation.
  • Evaluate base models and perform post-training or fine-tuning to meet specific performance targets.
  • Improve model accuracy, latency, and cost-effectiveness across real-world document workflows.
  • Design and maintain benchmarks to measure extraction quality, layout understanding, optical character recognition performance, reasoning accuracy, and end-to-end system reliability.
  • Work with real-world documents, including PDFs, scanned documents, tables, charts, forms, and multi-page enterprise documents.
  • Collaborate with engineering to move successful research prototypes into production.
  • Work directly with customers when needed to translate product requirements into benchmarks, experiments, and model improvements.
  • Stay current with research in vision-language models, document AI, post-training, synthetic data, and agentic systems.
  • Use modern AI coding workflows and tools to work efficiently.

Desired Qualifications

  • Prior startup experience, especially at an early-stage or high-growth AI company.
  • Experience as a founder or early startup engineer.
  • Experience building or improving document processing systems.
  • Experience with synthetic data generation, post-training, fine-tuning, or benchmark design.
  • Familiarity with tools such as vLLM, Pydantic, uv, ruff, mypy, Claude Code, Cursor, or similar modern AI engineering workflows.
  • Experience with open-source AI infrastructure or developer tools.

About the Company

LlamaIndex

Connects data to large language models

LlamaIndex.ai builds a data framework that helps businesses connect their own data sources to large language models (LLMs). It supports integrating structured data (like Excel and SQL), semi-structured data from APIs (such as Slack, Salesforce, and Notion), and unstructured data (web pages and images) so LLMs can understand and draw insights from a company’s data. The product works by linking diverse data sources to LLMs, enabling queries and data-driven answers across a company’s systems. Compared with competitors, LlamaIndex.ai emphasizes flexible connectors and a unified framework to access multiple data types through LLMs, making it easier for businesses to leverage AI on their existing data without heavy custom engineering. The company’s goal is to help organizations make data-driven decisions by simplifying access to their data through AI-powered language models, typically via a subscription-based B2B model.

Company size
51-200
Company stage
Series A
Total funding
$27.5M
Headquarters
San Francisco, CA
Founded
2023

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