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Founding ML Researcher

david joseph & company United State
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AI Summary

Shape the company's ML research direction and translate cutting-edge research into production-ready document-AI models. Own the end-to-end ML lifecycle from research to production deployment, working directly with founders on product strategy. Build and optimize VLM-based document understanding systems for high-stakes finance, legal, and healthcare workflows.

Key Highlights
Founding ML Researcher role with full ownership of ML lifecycle from research to production
Production-grade document AI converting unstructured PDFs, PPTs, Excel into structured Markdown/JSON
Competitive compensation $200,000–$300,000 + equity, visa sponsorship available
Key Responsibilities
Own the end-to-end ML lifecycle: research experimentation training evaluation production deployment
Work with the engineering team to transition research into deployed, scalable systems
Drive best practices for data, experimentation, evaluation, and model iteration
Technical Skills Required
Machine Learning Document AI VLM-based document understanding Layout models
Benefits & Perks
Full health insurance
DoorDash/Uber credits
Company laptop

Job Description


San Francisco, CA

  • On-site
  • Full-time Compensation: $200,000–$300,000 + 0.1%–1% equity


About The Company

A seed-stage AI company converting complex, unstructured documents into clean, LLM-ready structured data. Production-grade APIs ingest, parse, structure, and split documents across formats (PDF, PPT, Excel) into Markdown and JSON that AI agents and LLMs can work with reliably — preserving document structure and hierarchy while capturing the domain-specific context critical for high-stakes workflows in finance, legal, and healthcare. Founded 2024

  • 1–10 people
  • Industry: AI Tools / Document AI


The Role

Founding ML Researcher shaping the company's ML research direction and translating cutting-edge research into production-ready document-AI models. Research-heavy but product-oriented — you'll be comfortable moving between theory, experimentation, and real-world deployment, with full ownership from idea to production.

What You'll Be Doing

  • Own the end-to-end ML lifecycle: research experimentation training evaluation production deployment
  • Work with the engineering team to transition research into deployed, scalable systems
  • Drive best practices for data, experimentation, evaluation, and model iteration
  • Work directly with the founders to shape product direction and engineering strategy


Tech stack: VLM-based document understanding, layout models, document parsing of unstructured data, and production model serving / inference optimization.

Requirements

  • Training and deploying state-of-the-art models for parsing and understanding unstructured data
  • Experimenting with novel techniques to improve layout models and VLM-based document understanding
  • Building data pipelines, evaluating model performance, and integrating models into production systems


Green Flags

  • Experience at top research labs like DeepMind, OpenAI
  • Strong publication record in computer vision/ML
  • Hands-on implementation and production experience


Red Flags

  • Candidates whose recent focus has been management, rather than individual contributor work
  • No hands-on experience training AI models


Why Join

  • Define the technical archetype for a small, talent-dense founding team
  • Full ownership of the ML lifecycle, from research through production
  • Direct collaboration with the founders on product and ML strategy
  • Ship models used in high-stakes finance, legal, and healthcare workflows
  • Competitive comp + equity, full health insurance, DoorDash/Uber credits, company laptop


Details

Location: San Francisco, CA

Work policy: On-site

Compensation: $200,000–$300,000 + 0.1%–1% equity

Experience: Any (new PhD grads are acceptable)

Visa sponsorship: H-1B, O-1, OPT

Employment type: Full-time

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