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TalentGenius, headquartered in Austin, TX, is on the hunt for a Data Scientist with expertise in Large Language Models (LLMs) and Generative AI. The role involves joining a global AI and Data Intelligence team aimed at improving their career management platform using state-of-the-art data and AI technology. Candidates should be ready for a dynamic role within a fast-paced and collaborative environment.
The new Data Scientist will lead the development and implementation of machine learning algorithms, focusing especially on NLP and Generative AI. Key tasks include maintaining state-of-the-art AI model knowledge, data analysis, model benchmarking, documentation, and collaboration with cross-functional teams for successful AI model implementation.
The candidate will be tasked with implementing the LLM strategy, ensuring data accuracy, and deriving insights essential for both the Technology and Marketing teams at TalentGenius. They will turn complex datasets into actionable insights and integrate solutions with the TalentGenius infrastructure.
Prospective candidates should possess an advanced degree in a relevant field and a minimum of 2 years of applied experience in machine learning or a related domain. Proficiency in LLM and Transformer techniques, programming in languages like Python or R, and experience with AI platforms are necessary. Knowledge in SQL and relational database architecture, and familiarity with software development practices are also required.
Qualified individuals who are proficient in English and demonstrate strong communication and analytical skills are encouraged to apply through the provided remote job link.
This role offers a significant opportunity to work on AI-powered projects, contributing to revolutionary products in the HR industry and career management services.
This job offer was originally published on We Work Remotely
This job offer summary has been generated using automated technology. While we strive for accuracy, it may not always fully capture the nuances and details of the original job posting. We recommend reviewing the complete job listing before making any decisions or applications.
