Job Description

Our client is building the ingestion layer between raw enterprise data and AI. The company specializes in transforming unstructured documents—such as PDFs, spreadsheets, and scanned forms—into structured, LLM-ready data with exceptional accuracy.

Reducto’s platform is trusted by both high-growth startups and Fortune 10 enterprises, including Airtable, Scale AI, and a top FAANG company. Processing tens of millions of pages each month, its document AI system has become the go-to solution for teams deploying large language models in production environments.

With $33M in funding from top-tier investors like Benchmark and industry leaders from Dropbox, Airtable, and Google Gemini, Reducto is built for long-term scale and impact. This is a rare opportunity to join an early, high-agency team building mission-critical machine learning systems used in the real world—not just demos. The company operates in person from San Francisco and values performance, precision, and product-driven ML innovation.

Roles and Responsibilities:

• Build and deploy ML models for document processing
• Work on vision-language models, OCR, and LLM integrations
• Push boundaries in document AI with production-ready solutions
• Help architect the ingestion layer between unstructured data and LLMs
• Contribute to infrastructure and scalability

Job Requirements:

• 2–5 years experience in ML engineering
• Strong Python skills
• Experience deploying ML models to production
• Experience with LLMs, CV models, OCR, VLMs
• CS degree from a top school
• Experience in high-stakes domains (healthcare, finance, gov)
• Strong software engineering foundations
• In-office availability 5 days/week in SF

Job Tags

Similar Jobs