AI Analytical Automation Engineer

About the role

Implement, manage and support/maintain the AI large language models in MPS.

Responsibilities

• Responsible for the end-to-end technical implementation of enterprise-level large language model projects, including solution design, implementation, deployment, and optimization.
• Enhance model training and inference efficiency through Prompt engineering, model fine-tuning (e.g., LoRA, QLoRA), and performance evaluation.
• Utilize technologies like LangChain, RAG, and Agent to build AI systems, and perform model performance optimization (e.g., quantization, distillation).
• Track and research latest technological advancements in the industry to maintain technical leadership.
• Other assignments from Supervisor.

Requirements

• Technical Foundation: Solid foundation in machine learning/deep learning; proficient in Python and PyTorch; familiar with Transformer architecture and NLP tasks.
• Core Skills: Proficient in Prompt Engineering and LLM fine-tuning techniques; experience building complex AI applications using frameworks like RAG and Agent.
• Engineering Capability: Familiar with model optimization techniques (e.g., quantization, pruning); proficient in development and deployment tools like Git and Docker; possesses cloud platform deployment experience.
• Comprehensive Skills: Experience with end-to-end project implementation; strong business acumen and cross-department communication skills.
• Good people and communication skills (English, Chinese).

Additional Information

Monolithic Power Systems, Inc. (MPS) is one of the fastest growing companies in the Semiconductor industry. We are worldwide technical leaders in Integrated Power Semiconductors and Systems Power delivery architectures. At MPS, we cultivate creativity, are passionate about sustainability, and are committed to providing leading-edge products and innovation to our customers. Our portfolio of technology helps power our world ---come join our team and see how YOU can make a difference. Job Description:

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