AI Research Engineer (Document AI)

TL;DR

AI Research Engineer (Document AI): Developing and training vision-language models for document processing with an accent on data curation, synthetic data generation, and benchmarking. Focus on building production-ready systems that improve model accuracy, latency, and cost-effectiveness for real-world document workflows.

Location: Must be based in or able to work from San Francisco (Hybrid)

Salary: $180,000 – $250,000

Company

A fast-growing AI startup focused on core infrastructure for document understanding and agentic systems.

What you will do

• Develop and train vision-language models for document understanding.
• Build data pipelines for curation, synthetic data generation, and benchmarking.
• Perform post-training and fine-tuning to meet performance targets.
• Optimize model accuracy, latency, and cost-effectiveness for production.
• Design benchmarks to measure extraction quality and system reliability.
• Collaborate with engineering to transition research prototypes into production systems.

Requirements

• 3–7 years of experience in machine learning engineering or applied research.
• Strong foundation in benchmarking and training models.
• Proficiency in Python and PyTorch.
• Experience with computer vision, vision-language models, NLP, or OCR.
• Ability to write clean, production-quality code.
• Must be comfortable working in a fast-paced startup environment.

Nice to have

• Prior experience in early-stage or high-growth AI companies.
• Experience with synthetic data generation and post-training workflows.
• Familiarity with modern AI tooling like vLLM, Pydantic, or Cursor.
• Experience building document processing systems.

Culture & Benefits

• Work on core AI infrastructure with high technical ownership.
• Collaborate directly with technical founders and an ambitious engineering team.
• Join a company with strong open-source adoption and commercial traction.
• Opportunity to influence product capability and technical direction.