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Deontic | NLP Engineer

NLP Engineer

San Francisco, CAOn-siteFull-time$140k – $220k / year

About this role

Deontic | NLP Engineer Leuven, Belgium Full-time Deontic is a generative AI company building a regulatory compliance toolkit and dashboard for Original Equipment Manufacturers, Vendors and Suppliers in the Autonomous Mobility space. We are seeking a highly skilled NLP Engineer to join our team. As an NLP Engineer, you will be responsible for developing and implementing natural language processing algorithms and models for our AI-powered compliance platform. Benefits - A chance to help shape the future of autonomous mobility by building safer self-driving cars, trucks and buses - A dynamic and creative working and well-being environment - The flexibility to work partially from home - A weekly company lunch, dinner or happy hour - All the software, hardware and T-shirt perks you need to help you get the job done - A competitive salary Responsibilities - Develop methods to collect, analyze and enrich compliance-related documents from a variety of sources - Collect, optimize and manage training and test data. Develop effective training and testing procedures - Build state-of-the-art NLP models, particularly for classification, search and question answering - Optimize the performance of our search engine and existing NLP models - Communicate with the product team and other stakeholders to translate functional requirements into a sound modeling approach - Optimize, deploy and monitor our NLP models in production - Stay up-to-date with the latest advancements in NLP and recommend best practices to the team Requirements - Master's degree in Computer Science, Computational Linguistics, or a related field - Excellent analytical and problem-solving skills - Strong programming skills in Python - 2+ years of experience in developing and implementing natural language processing algorithms and models using Python and NLP libraries (e.g., spaCy, scikit-learn, transformers by Huggingface) - Familiarity with machine learning algorithms and frameworks - Expe

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