Multimodal AI Engineer (Document Understanding)

TL;DR

Multimodal AI Engineer (Document Understanding): Develop and optimize machine learning models and production systems for document parsing and understanding with an accent on computer vision, NLP, and multimodal learning. Focus on designing scalable ML infrastructure, fine-tuning models, and integrating AI innovations into production APIs.

Location: Hybrid in San Francisco office with remote considered for exceptional fits

Salary: $180K–$250K plus equity

Company

Innovative AI startup focused on redefining document workflows with advanced AI agents and open-source frameworks.

What you will do

• Develop, train, and optimize ML models for document structure, table extraction, and layout analysis
• Build data pipelines, evaluation frameworks, and experimentation infrastructure
• Design and implement scalable production ML systems for complex document processing
• Stay updated on vision-language models and multimodal learning advances
• Collaborate with engineering teams to integrate ML innovations into APIs
• Contribute to open-source frameworks and enterprise products

Requirements

• 3-7 years experience in ML engineering or applied research
• Strong Python software engineering skills with production experience
• Experience training, fine-tuning, or deploying ML models in production
• Deep knowledge of computer vision, NLP, or multimodal learning
• Ability to read and implement research papers and technical specs
• Comfortable working in fast-paced environments and open-source collaboration

Nice to have

• Experience with vision-language models, transformers, LoRA/QLoRA fine-tuning
• Building evaluation frameworks and data quality pipelines
• Model serving frameworks and MLOps tools experience
• Document understanding, OCR, layout analysis expertise
• Contributions to open-source ML projects
• Experience with LLM applications and RAG systems
• Model optimization techniques knowledge
• Docker/Kubernetes and distributed systems experience
• Active participation in ML research community

Culture & Benefits

• Competitive base salary and equity compensation
• Comprehensive medical, dental, and vision coverage
• Unlimited paid time off policy
• Daily catered lunch and snacks in San Francisco office
• Budget for conferences, research materials, and professional development
• Access to cutting-edge compute resources and research tools