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Machine Learning Engineer

Develops and deploys ML models for parsing unstructured enterprise data like PDFs, focusing on training vision models, experimenting with LLMs, building data pipelines, and integrating into products. Requires 2+ years in production ML, Python proficiency, and computer vision expertise.

150k – 300kSan Francisco, CAML EngineeringOnsite2+ YOE

About the role

Responsibilities

  • Training and deploying new state of the art models for parsing and interpreting unstructured data
  • Experimenting with novel techniques to improve LLM accuracy
  • Build data pipelines, evaluate model performance, and integrate models into the product
  • Working directly with the founders and customers to shape the product direction and engineering strategy

Requirements

  • 2+ years of experience with training, fine tuning, and evaluating ML models used in production systems
  • Exceptional at Python or similar
  • Well versed with both traditional computer vision and VLMs
  • Build your own tools as needed—like a quick Streamlit app to test hypotheses or create a dataset
  • A quantitative approach to building products. Ability to debug, experiment, and iterate fast
  • Comfortable getting hands-on with the full development lifecycle, from ideation to shipping to users

Nice-to-haves

  • Prior experience founding a company or building products at early stages
  • Ambitious and driven, and care a lot about doing great work with great people
  • Keep up with the latest developments in ML/AI

Skills

PythonComputer VisionVision Language ModelsStreamlitMachine LearningLLMsData Pipelines

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