Position Summary
We are seeking talented AI Engineer to drive the end-to-end development of AI solutions across on-premises and cloud environments. This role involves hands-on coding, building and deploying AI models, developing AI agents and portals, and optimizing performance across GPU infrastructures. The engineer will apply best practices in software engineering, AI Ops, and SDLC to deliver scalable, reliable, and innovative AI services.
Responsibilities
AI Solution Development
- Design, code, and implement AI use cases that address business needs.
- Develop and maintain AI agents, portals, and models.
- Build and optimize communication protocols for seamless integration across systems.
Model Training & Deployment
- Train, fine-tune, and evaluate AI/ML models using open-source and enterprise frameworks.
- Deploy models in both on-premises and cloud environments.
- Apply AI Ops practices to monitor, maintain, and improve model performance.
- Evaluate and monitor on-premises GPU usage to ensure efficient resource allocation.
- Optimize AI model performance through tuning, scaling, and hardware utilization strategies.
- Apply best practices to scale out infrastructure by integrating new GPUs with existing GPU clusters.
- Apply SDLC principles to AI solution development, ensuring quality and maintainability.
- Follow best practices in coding, testing, and documentation.
- Collaborate with cross-functional teams to integrate AI solutions into enterprise systems.
- Stay updated with emerging AI technologies and open-source platforms.
- Contribute to the evolution of AI development standards and practices.
- Provide technical input to improve scalability, security, and efficiency of AI services.
Performance Optimization & GPU Management
- Evaluate and monitor on-premises GPU usage to ensure efficient resource allocation.
- Optimize AI model performance through tuning, scaling, and hardware utilization strategies.
- Apply best practices to scale out infrastructure by integrating new GPUs with existing GPU clusters.
Engineering Practices
- Apply SDLC principles to AI solution development, ensuring quality and maintainability.
- Follow best practices in coding, testing, and documentation.
- Collaborate with cross-functional teams to integrate AI solutions into enterprise systems.
Continuous Improvement
- Stay updated with emerging AI technologies and open-source platforms.
- Contribute to the evolution of AI development standards and practices.
- Provide technical input to improve scalability, security, and efficiency of AI services.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
- Minimum 3 years of experience in AI/ML development and engineering.
- Strong coding skills in Python, Java, or similar languages.
- Hands-on experience with open-source AI platforms (e.g., TensorFlow, PyTorch, Hugging Face).
- Familiarity with SDLC methodologies and AI Ops practices.
- Experience with cloud platforms (Azure, AWS, GCP) and on-premises infrastructure.
- Knowledge of communication protocols (REST, gRPC, WebSockets, etc.).
- Experience in GPU resource management, performance optimization, and scaling strategies.
- Good command of both Chinese and English. Proficiency in Cantonese is an advantage.
- Relevant HKIB qualification will be an advantage.
- Candidates with more experience may be considered as Senior AI Engineer
- The role can be based in Hong Kong, Shenzhen or Guangzhou
Personal data provided by job applicants will be used for recruitment purposes only and will be treated in accordance with the Bank's Personal Data Policy, which is available upon request. Applicants who are not invited for interviews within six weeks may consider their applications unsuccessful and the personal data collected will be destroyed after 1 year.