The Specialist I (AI Solutions) will report to the Manager (AI Solutions) and collaborate across departments to architect, build, and implement scalable AI/ML solutions that tackle key business objectives. This role requires hands-on technical proficiency, strong analytical capabilities, and the ability to convert complex models into reliable, production-grade systems.

Key Responsibilities
Data Engineering & Preparation
Acquire, preprocess, and engineer features from diverse data sources
Design and maintain robust data pipelines while ensuring adherence to data governance standards

Model Design & Evaluation
Explore, develop, and test machine learning and deep learning algorithms
Adapt commercial or open-source AI platforms (e.g., Azure ML, Hugging Face, Watsonx, Dify) to meet organizational needs
Conduct thorough model validation, fine-tuning, and bias/error assessments

Deployment & Integration
Partner with IT teams to containerize models, expose APIs, and embed AI capabilities into enterprise systems using CI/CD methodologies
Monitoring & Optimization
Set up monitoring tools to assess model accuracy, drift, and system performance
Continuously enhance models to ensure optimal performance and compliance with internal policies

Enablement & Documentation
Produce clear technical documentation and lead training sessions to empower teams in using AI tools effectively
Help define best practices and contribute to internal AI guidelines and frameworks

Research & Exploration
Keep pace with emerging AI research and industry innovations
Experiment with advanced AI techniques and recommend adoption when they offer measurable business impact
Carry out additional tasks as directed by supervisor(s)

Qualifications
Bachelor’s degree or higher in Computer Science, Information Technology, Artificial Intelligence, Fintech, or related fields
At least 3 years of practical experience in AI engineering, machine learning, or data science, ideally in corporate environments
Demonstrated portfolio of deployed AI models (e.g., GitHub repositories, project summaries)
Skilled in Python or R, with hands-on experience using ML libraries (TensorFlow, PyTorch, scikit-learn), SQL, and cloud-based AI/ML platforms (AWS, Azure, GCP); familiarity with MLOps tools such as Docker, Kubernetes, MLflow
Strong analytical mindset with solid grounding in statistics, data ethics, and governance principles
Excellent communication skills with the ability to distill technical concepts into actionable business insights
Proficient in both English and Chinese; fluency in Putonghua is a plus

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