S

SAS

Analytics, BI, and data management software

Data Scientist Intern

AI Application EngineeringPosted on Nov 6
Internship · Summer 2027Cary, NC, USA$29 - $49 /hr

About the Job

Requirements

  • You must be currently pursuing a Master's or PhD, enrolled in an accredited program, and not graduating before December 2027.
  • You must currently be studying Computer Science, Electrical Engineering, or a closely related field.
  • You must have experience with Python and Generative AI foundation models such as GPT or Claude.
  • You must have strong written and verbal communication skills.
  • You must demonstrate leadership abilities and initiative through past experience.
  • You must be interested in the future of analytics and embrace technology.

Responsibilities

  • Build Generative AI models using large language models (LLMs) and/or visual language models (VLMs) to address SAS customer challenges.
  • Use libraries such as LangChain and LangSmith to build applications leveraging LLMs and VLMs.
  • Collaborate with data scientists and assist with prompt engineering and Retrieval-Augmented Generation (RAG) workflows to solve customer business problems.
  • Research and develop high-quality demos illustrating practical applications of Generative AI.
  • Optimize the deployment pipeline for Generative AI models.
  • Work as part of a team with specialized skills in machine learning, deep learning, natural language processing, and computer vision.

Desired Qualifications

  • Experience developing and deploying large language models (LLMs), and experience with PyTorch, TensorFlow, NVIDIA CUDA, or SAS.
  • Experience with practical implementations of LLMs and advanced analytics projects.
  • Experience with bash scripting, Docker, and Kubernetes.

About the Company

SAS

Analytics, BI, and data management software

SAS provides analytics, business intelligence, and data management software and services to organizations across government, business, and academia. Its products cover data mining, statistical analysis, forecasting, and optimization, and are sold as software licenses, with accompanying training, consulting, and support services. The platform typically helps users analyze large data sets and turn insights into decisions through a full analytics lifecycle—from data preparation to modeling and deployment. SAS differentiates itself through its long history (founded in 1976) and a broad, enterprise-grade suite with extensive services and a global presence that serve many of the world’s largest organizations. Its goal is to help customers become data-driven by turning data into actionable insights that improve decision making and outcomes.

Company size
10,001+
Company stage
Grant
Total funding
$1M
Headquarters
Cary, NC
Founded
1976

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