Machine Learning Engineer

Join a machine learning team building vision models that interpret complex documents and make their contents useful to language models. You will own models end to end, from research and experimentation through production deployment, working on real-world enterprise workloads.

• Build and deploy models for parsing and interpreting unstructured data.

• Experiment with techniques to improve language model accuracy and develop tools to measure results.

• Create data pipelines, evaluate model performance, and integrate models into the product.

• Contribute to product direction and engineering strategy in collaboration with company leadership and customers.

• At least 4 years of full-time machine learning engineering experience after graduation.

• Experience training, fine-tuning, and evaluating machine learning models for production systems.

• Hands‑on experience with OCR and document understanding, as well as computer vision, vision-language models, or large language models.

• Strong Python skills and experience building with machine learning tools and frameworks;
  Streamlit experience is relevant.

• A background in a startup or other environment outside large technology companies, with practical ownership of models shipped to users.

• Strong computer science or engineering fundamentals.

• Research publications in computer vision, vision-language models, or document understanding are a plus.

Base salary is $200,000 to $325,000 annually. Visa sponsorship is available.

Remote within the United States, with San Francisco as the primary location.