In This Role, Your Responsibilities Will Be:- Support deployment, optimization, and performance improvement of large language and multimodal models in internal “intelligent” use cases (such as knowledge search, content drafting, and productivity assistants).

• Package and integrate large model APIs into internal applications and business workflows to enable intelligent upgrades across functions.
• Help organize and structure internal knowledge assets (documents, FAQs, wikis), build an efficient retrieval experience, and improve model responses using retrieval‑augmented generation (RAG) techniques.
• Research, test, and refine high-quality prompts to improve task execution, controllability, and output quality across different scenarios.
• Develop proof‑of‑concept and production-ready AI capabilities such as smart Q&A, document generation, summarization, and code assistance—focusing on usability, reliability, and measurable value.
• Stay current on advances in large language models and multimodal AI, and help evaluate emerging tools and approaches for responsible adoption within the company.

Who You Are: You learn quickly and apply new ideas to real problems, experimenting thoughtfully and improving solutions based on results. You build collaborative relationships, communicate clearly, and enjoy partnering with others to deliver outcomes. You balance curiosity with practical execution, using data and feedback to iterate and improve. You take ownership of your work, follow through on commitments, and look for ways to simplify processes and help teams work more effectively.
For This Role, You Will Need: - Currently pursuing a degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related field (or equivalent hands-on experience through projects).

• Familiarity with Python and/or another programming language used for prototyping and integration.
• Basic understanding of large language models and common GenAI concepts (e.g., embeddings, prompt design, evaluation, hallucination risks).
• Ability to communicate effectively in English (written and verbal) and collaborate with cross-functional stakeholders.
• A structured, detail-oriented approach to problem solving, documentation, and testing.

Preferred Qualifications That Set You Apart:- Experience building with GenAI frameworks or toolkits (e.g., Lang Chain, Llama Index) and implementing RAG pipelines.

• Exposure to API integration, microservices, or workflow automation; familiarity with containers (Docker) is a plus.
• Understanding of search/retrieval fundamentals (vector databases, indexing, ranking) and practical evaluation methods.
• Experience developing internal tools (chatbots, knowledge assistants) with attention to security, privacy, and access control.
• Interest in multimodal AI (text + image/document processing) and techniques to optimize latency and cost

Our Culture & Commitment to You: At Emerson, we prioritize a workplace where every employee is valued, respected, and empowered to grow. We foster an environment that encourages innovation, collaboration, and diverse perspectives—because we know great ideas come from great teams. As an intern, you will receive guidance, feedback, and opportunities to learn through real-world projects that make a meaningful impact.We recognize the importance of wellbeing and belonging. Emerson supports employees through inclusive communities, recognition programs, and benefits designed to help people thrive. We are committed to creating an environment where you can do your best work, develop your skills, and build a strong foundation for your career.