Machine Learning Engineer
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
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