Generative AI Implementation Intern

InterDigital, Inc.Conshohocken, PA
2dOnsite

About The Position

About InterDigital InterDigital is a global research and development company focused primarily on wireless, video, artificial intelligence (“AI”), and related technologies. We design and develop foundational technologies that enable connected, immersive experiences in a broad range of communications and entertainment products and services. We license our innovations worldwide to companies providing such products and services, including makers of wireless communications devices, consumer electronics, IoT devices, cars and other motor vehicles, and providers of cloud-based services such as video streaming. As a leader in wireless technology, our engineers have designed and developed a wide range of innovations that are used in wireless products and networks, from the earliest digital cellular systems to 5G and today’s most advanced Wi-Fi technologies. We are also a leader in video processing and video encoding/decoding technology, with a significant AI research effort that intersects with both wireless and video technologies. Founded in 1972, InterDigital is listed on Nasdaq. InterDigital is a registered trademark of InterDigital, Inc. For more information, visit: www.interdigital.com. About the Team The AI Resource Group is building practical generative AI solutions that help product and business teams work smarter. We partner with employees across the company to turn everyday challenges into AI-powered workflows—focusing on adoption, enablement, and measurable impact. Role Summary As a Generative AI Implementation Intern, you'll work directly with employees to teach prompt engineering and AI best practices, identify high-impact use cases, and build production-ready automations that improve team efficiency. This is a collaborative, customer-facing role: you'll coach users, prototype solutions, document patterns, and lead knowledge-sharing activities so the organization can adopt AI responsibly and at scale. You'll report to a senior member of the AI Resource Group who will serve as your mentor throughout the internship.

Requirements

  • Currently enrolled in a Bachelor's or Master's program in Computer Science, Data Science, AI/ML, Human-Computer Interaction, Information Systems, or a related field
  • Hands-on experience with LLMs, generative AI workflows, and prompt engineering
  • Excellent communication skills—able to translate technical concepts into clear, actionable guidance for non-technical users
  • Strong facilitation and interpersonal skills; comfortable presenting to groups
  • Familiarity with Python and experience calling language model APIs (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face)
  • Comfortable building quick prototypes (Jupyter/Colab, scripts, small web UIs) with familiarity in Git and basic software development practices
  • Able to work on-site in Conshohocken, PA for the duration of the internship
  • Authorized to work in the United States

Nice To Haves

  • Experience building chatbots, assistants, or integrations (e.g., Slack bots, Teams bots, small web apps)
  • Knowledge of LLM evaluation metrics, hallucination mitigation strategies, and prompt-based safety/guardrails
  • Coursework or practical experience in AI ethics, responsible AI, or data governance

Responsibilities

  • Coach and enable: Deliver 1:1 sessions and workshops on prompt design, LLM workflows, and generative AI best practices for technical and non-technical audiences.
  • Discover opportunities: Facilitate use-case discovery with business and engineering teams to identify where AI can increase productivity or improve outcomes.
  • Build and ship: Design, prototype, and deploy custom GPTs, assistants, and lightweight automations that solve real user problems.
  • Create reusable resources: Develop a curated prompt library, templates, playbooks, and demo videos that propagate best practices across the organization.
  • Measure and improve: Implement evaluation checks for outputs (accuracy, relevance, hallucination mitigation) and track metrics on usage and efficiency gains.
  • Collaborate on governance: Work with engineering and security teams to ensure all prototypes follow data governance, privacy, and responsible-AI policies.
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