Machine Learning
4 days ago
We're looking for an experienced Machine Learning Engineer to design, build, and deploy scalable ML solutions while ensuring compliance with AI governance and responsible AI practices. It covers the full ML lifecycle from data pipelines and ML Operations deployment to model monitoring and stakeholder collaboration in a global banking environment.
Client Details
Our client is a globally established financial institution with a major technology hub in Asia. They play a critical role in supporting international banking operations through the development of in-house applications and enterprise-level digital initiatives. With strong regional integration and a forward-looking tech strategy, they continue to enhance operational efficiency and drive innovation across global markets.
Description
Key Responsibilities:
- Partner with data scientists and business teams to define ML solutions and develop Proof of Concepts.
- Deploy and manage ML models in production using ML Operations best practices (CI/CD, monitoring, versioning).
- Build and maintain scalable data pipelines while ensuring model performance and reliability.
- Ensure compliance with AI governance, responsible AI practices, and audit requirements.
- Support data exploration, feature engineering, and model development when required.
- Automate retraining, testing, and monitoring to sustain long-term model accuracy.
- Document ML workflows and collaborate with DevOps, IT, and security teams for enterprise integration.
Profile
A successful candidate should have:
- Have Master's degree in AI/ML or data science with proven model design and development expertise.
- At least 6 years' experience in data science and ML, including at least 3 years in ML engineering roles.
- Hands-on experience across the full ML lifecycle: data preparation, model development, deployment, and monitoring.
- Strong Python programming skills and familiarity with ML frameworks (scikit-learn, TensorFlow, PyTorch).
- Proficiency in NoSQL databases (Graph DB experience a plus) and use of ML Operations tools (MLflow, Airflow, Kubeflow, etc.).
- Experience with cloud platforms (AWS, GCP, Azure), CI/CD pipelines, and containerization (Docker, Kubernetes).
- Knowledge of responsible AI practices, governance, compliance, and techniques like NLP, time series, and supervised/unsupervised learning.
- Strong problem-solving, communication, and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders in diverse environments.
Job Offer
Why this role?
- Opportunity to work on cutting-edge AI/ML projects within a global banking environment
- Exposure to enterprise-scale ML Operations practices and full ML lifecycle implementation
- Career growth through continuous learning and professional development
- Competitive compensation and attractive benefits package
- Collaborative and multicultural workplace culture
To apply online please click the 'Apply' button. For a confidential discussion about this role please contact Cheryl Sim (Lic No: R / EA No.: 18C9065) on Michael Page International Pte Limited, company number N (including Page Executive A) and Page Personnel Recruitment Pte Ltd (Registration Number: C)) operates under the EA Licence Numbers of 18S9099 and 18C9065.
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