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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