Associate Vice President AI and ML Modeling and Engineering

Alliance Bank Malaysia Berhad; Kuala Lumpur; On-site; MYR 80,000 - 100,000; Full time

Job summary

A leading Malaysian financial institution in Kuala Lumpur seeks an experienced AI/ML Engineer to develop machine learning models and collaborate closely with innovation partners. This role involves validating model performance and ensuring compliance with data governance standards. Candidates should have over 5 years of experience in AI/ML engineering and strong skills in data architecture and model lifecycle. The position offers opportunities for impact and innovation in the banking sector.

Qualifications

• Expertise in machine learning frameworks and MLOps.
• Strong analytical and problem-solving skills.
• Agile development and experimentation.
• Effective collaboration and communication.
• AI/ML model lifecycle and deployment.
• Data architecture and governance.
• Banking use cases and customer behavior modeling.
• Cloud platforms and integration tools.
• 5+ years in AI/ML engineering or data science.
• Strong understanding of software development, SLM, RPA, AI/ML, cloud infrastructure, and data governance.
• Proven track record in building machine learning models or SLM interfaces.

Responsibilities

• Develop Machine Learning Models with enterprise-grade platforms.
• Collaborate with Innovation Partners to define use case logic.
• Validate model accuracy and scalability.
• Support post-MVP rollout and continuous learning.
• Align with data infrastructure and governance standards.

Skills

Machine learning frameworks

Analytical and problem-solving skills

Agile development

Collaboration

AI/ML model lifecycle

Data architecture and governance

Banking use cases

Cloud platforms

5+ years in AI/ML engineering

Understanding of software development

Job description

Overview

Supports the Head, Innovation Hub to drive AIC agenda, experimentation & full-scale investments into proven transformative initiative that is aligned to targeted outcome

Responsibilities

Develop Machine Learning Models. Build and train ML models using enterprise-grade platforms. Apply supervised, unsupervised, and reinforcement learning techniques based on the business problem and data availability. Optimize model architecture for performance, interpretability, and deployment readiness.

Collaborate with Innovation Partners to Define Use Case Logic. Work closely with Innovation Partners to translate business challenges into AI use cases. Define model objectives, input/output structures, and success metrics in alignment with digital transformation goals. Ensure that use case logic is grounded in real-world operational needs, especially across consumer and SME banking domains.

Validate Model Accuracy and Scalability. Conduct rigorous testing to assess model accuracy, precision, recall, and other performance metrics. Perform stress testing and scalability assessments to ensure models can handle production-level data volumes and variability. Document validation results and iterate based on feedback from stakeholders and AIML engineers.

Support Post-MVP Rollout and Continuous Learning. Monitor model performance post-deployment and implement feedback loops for continuous learning and improvement. Collaborate with DevOps and data teams to ensure seamless integration into production environments. Maintain version control and retraining pipelines to adapt to evolving data and business conditions.

Align with Data Infrastructure and Governance Standards. Ensure all modeling activities comply with internal data governance policies, including data privacy, lineage, and access controls. Work within approved data infrastructure frameworks to ensure secure and compliant model development. Collaborate with data stewards and governance leads to maintain auditability and transparency of AI models.

Qualifications

• Expertise in machine learning frameworks and MLOps
• Strong analytical and problem-solving skills
• Agile development and experimentation
• Effective collaboration and communication
• AI/ML model lifecycle and deployment
• Data architecture and governance
• Banking use cases and customer behavior modeling
• Cloud platforms and integration tools
• 5+ years in AI/ML engineering or data science
• Strong understanding of software development, SLM, RPA, AI/ML, cloud infrastructure and data governance
• Proven track record in building machine learning models or SLM interfaces

Company Overview

Alliance Bank Malaysia Berhad and its subsidiary, Alliance Islamic Bank Berhad, offers banking and financial solutions through its consumer, Islamic banking. The Bank provides easy access to its broad base of customers throughout the country via multi-pronged delivery channels including retail branches, Privilege Banking Centres, Business Centres, Investment Bank branches, and mobile and Internet banking.