The Role
Develops and deploys machine learning and deep learning solutions, including data pipelines, model validation, MLOps, monitoring, and governance. The role customizes AI tools, integrates models into enterprise systems, documents technical standards, trains internal teams, and evaluates emerging AI techniques for business adoption.
Summary Generated by Built In
- Conduct data collection, cleaning, and feature engineering
- Establish data pipelines and ensure data quality and governance compliance
- 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, hyper-parameter tuning, and bias/error analysis
- 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
- Implement monitoring frameworks to track model performance, drift, and resource utilization
- Continuously refine models to maintain accuracy, efficiency, and compliance with governance policies
- Create technical documentation, run workshops, and support internal teams in understanding and leveraging AI tools
- Contribute to the development of AI standards and playbooks
- 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)
Requirements
- University degree preferably in Information Technology, Computer Science Fintech, Artificial Intelligence, or related disciplines
- At least 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
Skills Required
- University degree in Information Technology, Computer Science, FinTech, Artificial Intelligence, or a related discipline
- At least 3 years of hands-on experience in machine learning, data science, or AI engineering, preferably in enterprise environments
- Portfolio of deployed models, such as GitHub repositories or case studies
- Proficiency in Python or R
- Experience with machine learning frameworks and libraries including TensorFlow, PyTorch, and scikit-learn
- Proficiency in SQL
- Experience with cloud AI/ML services including AWS, Azure, or GCP
- Experience with MLOps tools including Docker, Kubernetes, and MLflow
- Strong problem-solving skills and statistical knowledge
- Familiarity with data governance and ethical AI considerations
- Ability to translate technical details into business-relevant insights
- Good written and spoken English and Chinese
- Proficiency in Putonghua
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The Company
What We Do
Teki'Spire Limited is an executive search and recruitment firm specializing in Technology, Data & Digital roles, covering functions such as Digital, Big Data, Business Intelligence, Application Development, and Project Management.
