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 WD thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution. WD is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at  jobs.accommodations@wdc.com  to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying. Notice To Candidates: Please be aware that WD and its subsidiaries will never request payment as a condition for applying for a position or receiving an offer of employment. Should you encounter any such requests, please report it immediately to  WD Ethics Helpline  or email compliance@wdc.com . ... (truncated, view full listing at source)