AI Acceleration Intern – AI Development Lifecycle

atZoetisRemoteUS flagUnited StatesInternshipArtificial IntelligenceEntry-level$16 – $40/hour

Posted 1 day ago

This is a fully remote position, open to applicants in United States.

📋 Description

• Assist in the planning and execution of AI pilots and proofs of concept, focusing on milestone tracking, user feedback collection, and summarizing findings and lessons learned.

• Collaborate with the AI Architect to document and improve AI development lifecycle standards, templates, and playbooks across various stages, including idea generation, proof-of-concept, pilot, and production.

• Analyze the AI use case pipeline to assess stage health, cycle times, and throughput, and create dashboards or reports to monitor key acceleration metrics.

• Aid in the preliminary assessment of new AI use cases by investigating AI tools and platforms and contributing to value assessments and business cases.

• Help prepare updates and materials for leadership meetings, including those for the AI Council.

• Create and present a final project for the internship to the team.


⛳️ Requirements

• Currently enrolled in a Bachelor’s or Master’s degree program in Computer Science, Data Science, Information Systems, Computer Engineering, Software Engineering, Business Analytics, or a related discipline.

• Fundamental understanding of artificial intelligence and machine learning concepts, including generative AI and large language models (LLMs).

• Familiarity with cloud or data platforms such as Microsoft Azure, AWS, or Databricks is advantageous.

• Knowledge of the software development lifecycle (SDLC) or Agile methodologies.

• Preferred experience with Python, SQL, Jira, or Confluence.

• Excellent analytical, writing, and communication abilities, with the capacity to convey technical concepts clearly to diverse audiences.

• Passion for responsible AI, AI governance, and the development and scaling of enterprise AI solutions.


🏝️ Benefits

• Opportunities for professional development and learning.

• Exposure to cutting-edge technologies and methodologies in AI.

• Collaborative and inclusive work environment.

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