Scope of Responsibilities
- Inform and implement the design and development of NLP applications to enhance the intelligence and efficiency of our data analytics software-as-a-service platform
- Review, verify, and aggregate the most appropriate annotated datasets for the best-supervised learning methods
- Ability to work with taxonomy experts to create and validate dataset annotation
- Use well-formed and effective text representation to change and adapt natural language documents into user-friendly features
- implement the latest technology to improve user search functionality as well as integrate state of the art LLM models into our Ark.ai platform to enhance user experience.
- Develop new algorithms and modeling techniques and conduct sound experiments to verify model results and integrate models into the live production system
- Establish meaningful criteria for evaluating algorithm performance and suitabilityImplement working, scalable, production-ready models and code
- Keep up to date with Machine Learning best practices and evolving open-source frameworks
- Regularly seek out innovation and continuous improvement, finding efficiency in all assigned tasks
- Collaborate closely with fellow taxonomists, software engineers, data scientists, data engineers, and QA engineers
Qualifications
- US Citizenship is Required
- Advanced degree, or bachelor’s with at least 3 years of experience, in Data Science, Machine Learning or a related field
- Minimum 3 years experience with hands-on development of NLP models
- In-depth understanding of NLP methods for text representation, semantic extraction techniques, data structures, and modeling
- Practical experience in building, developing, and productionizing both supervised and unsupervised machine learning models
- Advanced software skills in Python
- Advanced ability in forming SQL queries
- A strong desire to learn, investigate, and implement cutting-edge technologies
- Ability to work collaboratively throughout the design process.
- Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
- Experience in or exposure to the nuances of a startup or other entrepreneurial environment
- Experience in deploying ML models in Kubernetes environments
- Experience developing custom training sets for large language models
- Experience productionizing transformer-based models
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