Job Description

Job Responsibilities:
- Design and develop enterprise-level AI application systems to drive the deep integration of artificial intelligence into manufacturing and business scenarios.
- Build systems such as intelligent quality inspection, predictive maintenance, knowledge Q&A, and intelligent production scheduling based on large language models (LLMs), machine learning, and computer vision technologies.
- Oversee AI model deployment, system performance optimization, and stability assurance to ensure system scalability and sustainable operation, with the ability to resolve performance bottlenecks and accuracy degradation issues.
- Build enterprise-level AI capability platforms, such as Agent systems, RAG knowledge bases, data hubs, and capability hubs.
- Perform model compression and performance optimization to meet model performance and quantification requirements.
- Collaborate across teams to ensure the stable implementation of model optimization solutions in products.
- Participate in discussions with clients and product teams to identify new business use cases and value opportunities through POCs and rapid experiments.
- Write technical documentation, experiment reports, and method summaries to support team decision-making and knowledge accumulation.

Qualifications

Job Requirements:
- Master’s degree or higher in Computer Science, Machine Learning, Electronic Information, Intelligent Manufacturing, or a related field;
- 2+ years of AI development or related experience; candidates with experience implementing AI projects in the semiconductor manufacturing industry will be given priority
- Proficient in Python; familiarity with at least one common machine learning library (e.g., NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow); strong coding and engineering skills
- Familiarity with mainstream large-model application development (e.g., OpenAI, Tongyi, GPT) and prompt engineering;
- Familiarity with RAG architecture and vector databases (e.g., Milvus, FAISS, Weaviate);
- Preference given to candidates familiar with large-model application development frameworks such as LangChain, LlamaIndex, or Dify;
- Familiarity with cutting-edge technologies such as Transformers, LLMs, and v-LLMs
- Proficiency in backend development (FastAPI, Flask, Django, etc.) and API system design
- Familiarity with Docker and Linux deployment environments; experience with local model deployment is a plus
- Strong problem-definition skills and an exploratory mindset, capable of formulating hypotheses, designing experiments, and validating feasibility in scenarios with limited precedents;
- Strong communication and cross-team collaboration skills, capable of working with front-end, back-end, SRE, product, and testing teams to drive projects forward
- CET-6 or equivalent English reading and writing proficiency, capable of reading English technical documentation and participating in basic communication
- Interest in intelligent scenarios for semiconductor testing, and a willingness to explore and implement new application directions with the team