Job Opening

Our client, a Financial Institution, is looking for high-caliber person to fill the position.

Data Engineering and Preparation; Conduct data collection, cleaning, and feature engineering; Establish data pipelines and ensure data quality and governance compliance
Model Development and Validation; Research, prototype, and implement machine learning and deep learning models; Customize off-the-shelf or open-source AI tools (e.g. Azure ML, Hugging Face, Watsonx, Dify) for business needs; Perform rigorous validation, hyperparameter tuning, and bias/error analysis; Integration and Deployment; Collaborate with IT teams to containerize models, build APIs, and integrate AI services into the company’s technology stack, adhering to CI/CD best practices
Performance Monitoring and Optimization; Implement monitoring frameworks to track model performance, drift, and resource utilization; Continuously refine models to maintain accuracy, efficiency, and compliance with governance policies
Knowledge Sharing and Support; Create technical documentation, run workshops, and support internal teams in understanding and leveraging AI tools; Contribute to the development of AI standards and playbooks
Research and Innovation; Stay current with academic research and industry trends; Pilot cutting-edge AI techniques and recommend their adoption where they deliver clear business value
Perform other duties as assigned by supervisor(s)

University degree preferably in Information Technology, Computer Science Fintech, Artificial Intelligence, or related disciplines
Minimum of 3 years of hands-on experience in machine learning, data science, or AI engineering roles, preferably within enterprise environments
Portfolio of deployed models (GitHub, case studies)
Proficiency in Python or R, machine learning frameworks and libraries (TensorFlow, PyTorch, scikit-learn), SQL, and experience with cloud AI/ML services (AWS, Azure, GCP) and MLOps (Docker, Kubernetes, MLflow)
Strong problem-solving skills, statistical knowledge, and familiarity with data governance and ethical AI considerations
Effective communicator capable of translating technical details into business-relevant insights
Good command of written and spoken English and Chinese, with proficiency in Putonghua is an advantage

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