AI Research Engineer

Location: San Francisco, CA
Company Stage of Funding: Series A AI Infrastructure Company ($27.5M Raised)
Office Type: Hybrid (Monday, Wednesday, Friday In-Office)
Salary: $180,000–$250,000 + 0.1–0.4% Equity

Company Description

We're representing one of the leading companies in the AI infrastructure ecosystem, building the tools that enable developers and enterprises to create intelligent agents capable of understanding and acting on complex documents. Their platform combines state-of-the-art document processing, retrieval systems, and agent frameworks that power mission-critical workflows across financial services, consulting, healthcare, and other enterprise industries.

The company has experienced exceptional growth, scaling from zero to nearly $10M ARR in under two years while building one of the largest open-source communities in AI. With over 4 million monthly framework downloads and hundreds of millions of documents processed through their platform, they are helping define the future of document intelligence and enterprise AI applications.

What You Will Do

• Develop and train vision-language models that improve document understanding, extraction, and reasoning capabilities.
• Design datasets, synthetic data generation pipelines, and benchmarking frameworks for document AI applications.
• Evaluate foundation models and implement post-training techniques to improve performance on enterprise document tasks.
• Build and optimize agentic workflows that reason over complex documents and structured enterprise data.
• Design evaluation systems that measure model quality, accuracy, cost efficiency, and operational performance.
• Develop novel approaches to document parsing, information extraction, and multimodal reasoning.
• Build experimentation infrastructure that accelerates research velocity and model iteration cycles.
• Partner with customers to translate business requirements into measurable model capabilities and benchmarks.
• Collaborate closely with engineering and product teams to deploy research innovations into production systems.
• Contribute to the long-term evolution of the company’s document intelligence and AI agent platform.

Ideal Background

• 3–7 years of experience in machine learning engineering, applied AI research, or related technical fields.
• Strong experience training, evaluating, and deploying machine learning models in production environments.
• Deep understanding of modern machine learning techniques, including transformer architectures, multimodal models, and LLMs.
• Strong Python programming skills and proficiency with PyTorch or similar machine learning frameworks.
• Experience building evaluation systems, benchmarks, and experimentation frameworks.
• Familiarity with document processing, vision-language models, OCR systems, or multimodal AI applications.
• Demonstrated ability to operate independently and thrive in fast-paced startup environments.
• Strong technical communication skills and ability to explain research findings clearly.

Preferred

• Experience with document AI, document parsing, information extraction, or enterprise knowledge systems.
• Background in vision-language models, multimodal learning, computer vision, or agentic AI systems.
• Early-stage startup experience or previous founder experience.
• Academic research experience with publications in machine learning, NLP, computer vision, or related fields.
• Experience using AI-native engineering tools such as Claude Code, Cursor, or similar AI-assisted development workflows.
• Background from organizations such as OpenAI, DeepMind, Hugging Face, Unstructured, Instabase, Mindee, Mistral AI, top research labs, or quantitative trading firms.
• Familiarity with model serving, inference optimization, ONNX, TensorRT, Kubernetes, or large-scale AI infrastructure.
• Experience building production-grade AI agents and retrieval systems.

Compensation and Benefits

• Base salary: $180,000–$250,000.
• Equity: 0.1–0.4%.
• Hybrid work environment in San Francisco.
• Relocation assistance available for qualified candidates.
• Opportunity to work on one of the most widely adopted AI developer platforms in the ecosystem.
• Significant ownership over core AI research initiatives and product direction.
• Exposure to cutting-edge work in document intelligence, multimodal AI, and enterprise agents.
• Rapidly growing company with strong product-market fit and substantial career growth opportunities.
• Collaborative engineering culture focused on innovation, experimentation, and shipping impactful AI products.