Media Sputter process Engineer

• Prepare and maintain work instructions, process specifications, and change documents for sputter processes to ensure compliance with corporate quality systems and customer requirements
• Establish and continuously optimize CPK and process windows for critical parameters to ensure stable, consistent, and repeatable mass production processes
• Complete deployment and optimization of large models (vLLM/Qwen), AI Agents, WebUI, and MySQL integration
• Daily maintenance: service stability, GPU resources, model inference, database integration, log monitoring
• Iterative optimization: Agent capabilities, Prompt engineering, RAG, time series forecasting, production line data integration
• Production line integration: Understand coating processes and implement AI capabilities for production optimization
• Linux Systems: Proficient in Ubuntu, command line, Shell, Docker, docker-compose
• Large Model Deployment: vLLM, Open WebUI, local LLMs (Qwen/Llama/ChatGLM), model quantization (GPTQ/AWQ)
• AI Agent: LangChain/LangGraph, RAG, prompt engineering, tool calling
• Database: MySQL (SQL writing, connection, optimization, transactions); time series databases (InfluxDB/TDengine) are a plus
• Programming: Proficient in Python (FastAPI/Flask, Pandas, PyMySQL); knowledge of C++/CUDA is a plus
• GPU and Computing Power: CUDA, NVIDIA GPUs (H100/H200/A100), multi-GPU scheduling, memory optimization
• Industrial Scenarios: Familiarity with manufacturing/semiconductor/coating processes, PLC/production line data, MES/database integration is preferred

• Education: Bachelor’s degree or above (majors in Computer Science, Automation, Electronics, Mathematics, AI-related fields; Master’s preferred)
• Experience: 2–5 years (1–3 years for outstanding candidates; industrial AI/large model implementation experience preferred)
• Able to independently complete end-to-end deployment and troubleshooting of large models + Agents + databases
• Understand system stability, monitoring, logging, backup, disaster recovery
• Able to translate business requirements (coating process optimization) into AI capabilities
• Good communication skills, able to coordinate with production line engineers and technical teams
• Experience with industrial AI implementation projects (intelligent manufacturing, semiconductors, coating, chemical, etc.)
• Experience with local large model private deployment (no API, intranet security)
• Familiarity with time series forecasting (Moirai/Chronos, LSTM, Transformer)
• Experience with GPU clusters/multi-GPU scheduling
• Understanding of manufacturing databases/PLC/OPC UA

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