VP, AI/ML Modeling

1 day ago

Kuala Lumpur, Kuala Lumpur, Malaysia Alliance Bank Malaysia Berhad Full time $120,000 - $200,000 per year

Job Description

Develop Machine Learning Models

  • Build and train machine learning 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.

Requirement

  • 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

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