Job Description
Responsible for the construction of large-scale model infrastructure and the application implementation in business scenarios. Key responsibilities include but are not limited to:
- AI Infrastructure Development
- Design, select, and maintain company-wide large-scale model infrastructure, including cluster resource management, inference framework selection and optimization, base model selection, AI security and compliance systems, and AI gateway construction.
- Lead the development of LLM Agent and workflow orchestration platforms, providing low-code/standardized Agent development frameworks and toolchains to empower business teams to quickly build, test, and deploy intelligent agent applications.
- AI-Driven R&D Efficiency Improvement
- Build and promote AI-powered developer toolchains (e.g., R&D knowledge management, intelligent code review, AI operations assistant) to identify R&D bottlenecks through data-driven methods, significantly improving team efficiency and code quality.
- Responsible for evangelizing, training, and operating related tools and best practices, establishing evaluation systems to drive AI R&D culture within the company.
- AI-Business Scenario Integration
- Collaborate with business teams to explore LLM applications in intelligent customer service, data analysis, risk control, and marketing, completing technical solution design, prototype validation, and large-scale implementation.
- AI-Native Application Exploration
- Explore the integration of AI with CEX products, providing capabilities such as fundamental analysis, Trade Agent, DeFAI, and intelligent K-line charts to enhance C-end user experience.
Job Requirements
- Education & Experience
- Bachelor's degree or higher in Computer Science, Software Engineering, AI, or related fields.
- 5+ years of AI-related work experience, including at least 2 years in large-scale models.
- Technical Skills
- Solid computer science foundation, proficiency in at least one mainstream programming language, familiarity with computer networks, distributed systems, cloud-native technologies, and full software development lifecycle.
- Deep understanding of LLM principles and applications, with hands-on experience in at least 2 of: model training/inference, Agent frameworks, AI4SE, Data Agent, or RAG.
- Soft Skills
- Strong communication and collaboration skills to drive cross-departmental projects.
- Self-motivated problem-solver with a results-driven mindset.
- Passionate about technology and exploring cutting-edge AI applications.
Benefits
Please contact HR directly via Telegram for details!
Please contact HR directly via Telegram for details!
Please contact HR directly via Telegram for details!
Please contact HR directly via Telegram for details!
Please contact HR directly via Telegram for details!
