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Artificial Intelligence Engineer Intern Jobs (NOW HIRING)

Staffingine LLC

Artificial Intelligence Engineer

Bellevue, WA · On-site

$129K - $155K/yr

Job Title: Artificial Intelligence Engineer Job Location: Bellevue - Washington Job Type: Contract * Lead the development and deployment of machine learning models and analytical solutions for ...

SCATR Corp.

Artificial Intelligence Engineer

Cleveland, OH

$111K - $133K/yr

We are looking to add an experienced Artificial Intelligence (AI) Engineer to our dynamic team and contribute to the development of a robust AI-enabled solution. As an AI Engineer, you will be ...

1-800-Flowers

Intern, Artificial Intelligence

Jericho, NY · On-site

$19/hr

... Intern will support the Product & AI Innovation team by assisting with artificial intelligence ... Support data preprocessing, feature engineering, and dataset validation * Analyze structured and ...

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How much do artificial intelligence engineer intern jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for artificial intelligence engineer intern in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What does an Artificial Intelligence Engineer Intern do?

An Artificial Intelligence (AI) Engineer Intern assists in designing, developing, and testing AI models and algorithms under the guidance of experienced engineers. Their daily tasks may include data preprocessing, training machine learning models, evaluating model performance, and collaborating with team members on various AI projects. Interns often work with programming languages such as Python, and may utilize frameworks like TensorFlow or PyTorch. This role provides hands-on experience in applying AI techniques to real-world problems and helps interns build skills necessary for a career in artificial intelligence.

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Engineer Intern, and why are they important?

To thrive as an Artificial Intelligence Engineer Intern, you need a strong background in computer science fundamentals, programming (especially Python), and foundational knowledge of machine learning concepts, often supported by coursework or relevant projects. Familiarity with AI frameworks such as TensorFlow or PyTorch, experience with data analysis tools, and understanding of version control systems like Git are typically required. Curiosity, critical thinking, and effective communication help interns learn quickly, collaborate with teams, and contribute innovative ideas. These skills and qualities enable interns to contribute meaningfully to AI projects, adapt to new challenges, and build a solid foundation for a future career in AI engineering.

What types of projects and collaborations can an Artificial Intelligence Engineer Intern expect during their internship?

As an Artificial Intelligence Engineer Intern, you'll likely work on a variety of hands-on projects such as developing machine learning models, assisting with data preprocessing, and supporting the deployment of AI solutions. Interns often collaborate with cross-functional teams including data scientists, software engineers, and product managers to solve real-world business problems. You’ll gain exposure to production environments, code reviews, and may participate in team meetings or brainstorming sessions. This structure provides valuable experience and networking opportunities, while also allowing you to contribute meaningfully to ongoing projects.
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Artificial Intelligence Engineer

Prophecy Technologies

West Des Moines, IA • On-site

Full-time

Posted 2 days ago

Job description

Role Name: Artificial Intelligence Engineer
Location: West Des Moines-Iowa
Job Summary
We are seeking an experienced Artificial Intelligence Engineer to design, develop, and scale modern AI solutions leveraging GenAI, LLMs, and Agentic AI. The ideal candidate will work across data, engineering, and business teams to deliver intelligent applications, RAG pipelines, AI agents, and document automation workflows using AWS-native AI services.
Experience Range (Required Skills)
  • 5+ years in software engineering or data science.
  • 1+ year hands-on experience with GenAI, LLMs, or Agentic AI.
  • Proficiency in Python, REST APIs, and JavaScript/TypeScript frameworks (React, Node.js).
  • Experience working with cloud-native infrastructure: Docker, CI/CD pipelines.
  • Hands-on experience with AWS AI/ML services, including:
  • Bedrock
  • SageMaker
  • Textract
  • Translate
  • Lambda & other serverless components

Key Responsibilities
  • Design, build, and scale RAG pipelines, vector search architectures, and LLM evaluation workflows.
  • Develop intelligent AI agents using LangChain, AutoGen, LlamaIndex, or LangGraph.
  • Ingest, process, and prepare structured/unstructured data-chunking, embeddings, parsing, retrieval.
  • Create intuitive front-end experiences powered by LLM and agent-based intelligence.
  • Integrate enterprise AI tools such as:
  • Claude
  • GPT-4/4o / ChatGPT Enterprise
  • Copilot
  • Glean
  • Shelf
  • Drive advanced document automation, including summarization, translation, and named-entity recognition (NER).
  • Implement observability, governance, and responsible AI practices in compliance with enterprise regulations.
  • Partner with cross-functional teams (IT, data, risk, compliance, business) to deliver user-facing AI solutions.

Required Skills & Experience
  • Hands-on experience developing AI solutions using GenAI/LLM frameworks.
  • Strong expertise in Python and API development (REST).
  • Experience with modern frontend concepts (React, Node.js).
  • Knowledge of embeddings, vector stores, retrieval workflows, and LLM orchestration.
  • Experience with AWS AI services and cloud-native development patterns.

Competencies
  • Strong problem-solving and analytical thinking.
  • Excellent communication and collaboration across technical & business stakeholders.
  • Ability to work in fast-paced, innovation-driven environments.
  • Self-starter with strong ownership of solution delivery.

Preferred Skills
  • Experience with LangChain, AutoGen, LlamaIndex, or LangGraph.
  • Prior exposure to enterprise AI platforms such as Glean or Shelf.
  • Understanding of responsible AI, security, governance, and observability frameworks.
  • Experience building UI/UX for AI-driven applications.

Apply