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Job Description:
This person will be responsible for designing, developing, and deploying Service Supply Chain System AI Center, which dedicates to interact with business users and fully support their business seamlessly by providing “Insightful Analysis” with AI application.
The ideal candidate will be detail oriented and data driven to system developing and maintenance. And the candidate should have an ability to work effectively with cross-functional teams and an ability to work in a fast-paced and ever-changing environment.
The position represents an exciting opportunity to be a part of a dynamic and high paced environment, supporting a global organization and offers significant opportunities for rapid growth.
Job responsibilities
This role will involve:
1.Maintaining and improving the existing system to meet complexed and rapidly changed business scenario.
2.Establish the AI center to utilize AI technology for business functions such as demand forecasting, inventory monitoring, and process automation and more
3.Review business requirement document and develop automation solutions by using Java / SQL and other similar programming languages.
Job Requirement:
1.Bachelor or above Degree in Computer Science, Computer or Software Engineering, or related field.
2.5+ years of experiences AI or Java software development.
3.Responsible for designing innovative and highly efficient AI system architectures tailored to complex business scenarios, utilizing AI algorithms to enhance the system's decision-making capabilities and prediction accuracy, thereby meeting diverse business needs.
4.Good communication skills, good language skills in English.
5.Proficient in Python and familiar with PyTorch/TensorFlow frameworks.
Understanding of fundamental data structures and algorithms, with strong coding standards.
Basic Java coding skills are preferred.
6.Solid understanding of machine learning (e.g., classification/clustering) and deep learning (e.g., RNN/Transformer) theories.
7.Understanding of basic Agent architectures (e.g., task planning, memory management, tool invocation). Familiarity with frameworks such as LangChain and AutoGPT is preferred.
8.Knowledge of RAG (Retrieval-Augmented Generation), MCP/A2A multi-agent collaboration technologies.
9.Familiarity with mainstream large models (e.g., GPT, DeepSeek, LLaMA, ERNIE Bot) and fine-tuning methods. Basic experience in Prompt Engineering, capable of optimizing model outputs through prompt tuning. Understanding of lightweight model deployment (e.g., OLLMA, model quantization).