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Job Location drjobs

St. Louis, MO - USA

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Job Description

Title Data Scientist Information Retrieval Scientist (NLP/Python/LLM)

Client Location

St. Louis MO

Hybrid 3 days onsite

MUST BE LOCAL To St. Louis. (No Relocation)

Required

3 years Work experience Python

3 years Work experience NLP (Natural Language Processing) related to AI

3 years Work experience LLM (Large Language Models )

Project will be working with Chat GPT

Project working to Gen AI based model development for text and/or images.

Required either Ph.D. (or Masters with 4 years of post MS experience) CS EE Physics Mathematics Statistics or Analytics.

Description

Were seeking a talented and innovative NLP/Information Retrieval Scientist to join our team. In this role you will play a pivotal part in enhancing Large Language Models (LLMs) to provide more accurate contextaware and creatively curated responses with realworld applications.

As an NLP/Information Retrieval Scientist you will develop and to improve the usability and creativity of our LLM responses. You will collaborate closely with our multidisciplinary team of researchers and engineers to not only advance the technical aspects but also bring realworld relevance and creativity into our language models.

The successful candidate will use the latest innovations in NLP and LLM to propose software solutions to improve customer experience. The NLP Data Scientist will design and test algorithms conduct prototyping to evaluate possible scenarios leveraging computational and statistical techniques for the development of novel approaches for Text and Image Data. Required Skills:

  • Ph.D. (or MS with 4 years of post MS experience) Computer Science Electrical Engineering Physics Mathematics Statistics or an Analytics discipline.
  • Plus 3 years of work experience
  • Expertise with NLP or Information
  • Proficiency in Python or in another highlevel programming language
  • Experience in developing statistical and machine learning models for environmental and agronomical applications.
  • Familiarity with LLM
  • Experience analyzing and presenting complex data and proven problemsolving abilities.
  • Strong publication record in leading scientific journals

Employment Type

Full Time

Company Industry

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