AI Acceleration Intern - AI Development Lifecycle

Zoetis•US NJ Remote, NJ
•$16 - $40•Remote

About The Position

The AI Acceleration Intern – AI Development Lifecycle (AIDLC) will join the AI Hub within Zoetis Tech & Digital, a team focused on accelerating how AI ideas are evaluated, developed, and delivered across the organization. The internship provides hands-on exposure to the full AI development lifecycle, from initial idea and proof of concept through pilot and production. The intern will support AI pilots, document architecture standards and best practices, evaluate the health of the AI use case pipeline, and gain experience with how a global animal health company develops and scales AI responsibly. The position is U.S. remote, with a preference for candidates located on the East Coast and/or near the Parsippany, New Jersey headquarters. The internship includes developing and presenting a final project to the team. Hourly pay varies by degree level and location: listed rates range from $16.00 to $36.00 per hour, or $17.00 to $40.30 per hour for candidates in specified higher-rate locations.

Requirements

  • Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Computer Engineering, Software Engineering, Business Analytics, or a related field.
  • Basic understanding of artificial intelligence and machine learning concepts, including generative AI and large language models (LLMs).
  • Familiarity with the software development lifecycle (SDLC) or Agile methodologies.
  • Strong analytical, writing, and communication skills, with the ability to explain technical concepts clearly to different audiences.
  • Interest in responsible AI, AI governance, and the development and scaling of enterprise AI solutions.

Nice To Haves

  • Exposure to cloud or data platforms such as Microsoft Azure, AWS, or Databricks.
  • Experience with Python, SQL, Jira, or Confluence.

Responsibilities

  • Help plan and execute AI pilots and proofs of concept, including tracking milestones, gathering user feedback, and summarizing results and lessons learned.
  • Partner with the AI Architect to document and enhance AI development lifecycle standards, templates, and playbooks across the idea, proof-of-concept, pilot, and production stages.
  • Review the AI use case pipeline to evaluate stage health, cycle times, and throughput, and develop dashboards or reports to track key acceleration metrics.
  • Support early evaluation of new AI use cases by researching AI tools and platforms and contributing to value assessments and business cases.
  • Assist in preparing updates and materials for leadership forums, including the AI Council.
  • Develop and present a final internship project to the team.
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