Intern - Software Engineering
Emerson View all jobs
- Shanghai
- Training
- Full-time
- 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.
- 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.
- Experience building with GenAI frameworks or toolkits (e.g., LangChain, LlamaIndex) 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