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You will train and deploy vision models to interpret unstructured documents and integrate them into production systems. Additionally, you will develop data pipelines and collaborate with leadership to shape engineering strategy.
Join a machine learning team building vision models that interpret complex documents and make their contents useful to language models. You will own models from research and experimentation through production, helping deliver reliable performance on real-world enterprise workloads.
Train and deploy models for parsing and interpreting unstructured data.
Experiment with techniques to improve language model accuracy and build tools to measure results.
Develop data pipelines, evaluate model performance, and integrate models into the product.
Collaborate directly with company leadership and customers to shape product direction and engineering strategy.
At least 4 years of full-time machine learning engineering experience after graduation; internships, co-ops, and fellowships do not count.
Experience training, fine-tuning, and evaluating machine learning models for production systems.
Hands-on experience with OCR and document understanding, along with vision-language models, computer vision, or large language models.
Strong Python skills and experience bringing models all the way into use by customers.
Startup experience or a background working primarily outside large technology companies.
Strong computer science or engineering fundamentals.
First- or second-author publication in computer vision, vision-language models, or document understanding is a plus.
Base salary: $200,000 to $325,000 annually. Visa sponsorship is available.
Remote within the United States, with San Francisco as the primary location.
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