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1 день назад

Intern, Applied AI (2027)

22 - 26$
Формат работы
hybrid
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Intern, Applied AI (2027) (Generative AI/Enterprise AI): Building and evaluating enterprise AI agents, copilots, knowledge assistants, and retrieval solutions with an accent on RAG, semantic search, Azure AI, and responsible AI. Focus on prototyping AI solutions, integrating APIs and enterprise systems, analyzing knowledge sources, and creating evaluation frameworks for grounded and reliable responses.

Location: Libertyville, Illinois, USA; hybrid role requiring attendance at the Libertyville office at least 4 days per week during Summer 2027. Relocation assistance, housing, and transportation are not provided.

Salary: $22.00–$26.00 per hour

Company

hirify.global is an employee-owned healthcare products company developing, manufacturing, and marketing products for ostomy care, continence care, and critical care.

What you will do

  • Assist with designing, developing, configuring, and testing enterprise AI agents and copilots using Microsoft Copilot Studio, Azure AI technologies, Python, and APIs.
  • Build retrieval and knowledge solutions using RAG, knowledge graphs, enterprise search, document intelligence, semantic search, vector search, metadata filtering, and citations.
  • Evaluate AI quality across accuracy, relevance, grounding, retrieval, citations, consistency, and usability; document defects and recommend improvements.
  • Analyze SharePoint sites, documents, PDFs, spreadsheets, images, OCR needs, metadata, access controls, and indexing requirements.
  • Prototype AI solutions, research emerging models and frameworks, and support integrations with enterprise services, Azure Functions, data platforms, and business applications.
  • Document results, maintain test evidence, collaborate with IT, R&D, Quality, Data, Automation, and business teams, and present internship outcomes.

Requirements

  • Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, Information Systems, Engineering, or a related field, with continued enrollment after the internship.
  • Foundational knowledge of artificial intelligence, machine learning, generative AI, large language models, software development, data structures, databases, or APIs.
  • Experience with at least one programming language for data or application development, preferably C# or Python; ability to write maintainable code and troubleshoot technical issues.
  • Strong written and verbal communication skills, including the ability to explain technical concepts to technical and non-technical audiences.
  • Curiosity, initiative, attention to detail, willingness to learn, and ability to collaborate across functions.
  • Ability to work from the Libertyville, Illinois office at least 4 days per week.

Nice to have

  • Hands-on experience with generative AI, prompt engineering, AI agents, chatbots, RAG, embeddings, semantic search, or vector databases.
  • Exposure to Microsoft Copilot Studio, Microsoft Azure, Azure AI Search, Azure AI Foundry, Microsoft Fabric, Power Platform, or SharePoint.
  • Experience with REST APIs, JSON, Git, GitHub, CI/CD pipelines, cloud development environments, or Python AI and data libraries.
  • Experience evaluating AI/ML systems or designing test cases for accuracy, reliability, responsible use, privacy, security, and governance.
  • Previous internship, research, hackathon, or substantial academic project involving AI, data, automation, or software development.

Culture & Benefits

  • Work with AI architects, engineers, IT specialists, and business stakeholders in a collaborative corporate environment.
  • Gain experience with enterprise AI governance, responsible AI, security, privacy, human oversight, and regulated workflows.
  • Participate in projects involving knowledge agents, document intelligence, evaluation frameworks, digital twins, simulation, SharePoint, GitHub, and CI/CD.
  • Learn how enterprise generative AI solutions are identified, designed, built, tested, governed, deployed, and improved.
  • Relocation assistance, housing, and transportation are not provided.

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