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The Role
Develop and maintain machine learning models and AI applications, including data preprocessing, feature engineering, model training, debugging, and production deployment. Collaborate with cross-functional stakeholders to translate business needs into scalable AI/ML solutions. Apply LLM techniques such as tokenization, RAG, and reinforcement learning, while following coding standards, participating in code reviews, and continuously improving technical expertise.
Summary Generated by Built In
Develop and maintain AI/ML models and applications:
- Design and implement machine learning models tailored to specific business needs.
- Continuously monitor and update models to ensure they remain accurate and effective.
- Develop applications that integrate AI/ML models, providing end-to-end solutions for various use cases.
Perform data preprocessing, feature engineering, and model training:
- Clean and preprocess raw data to remove noise and inconsistencies, ensuring high-quality input for models.
- Apply feature engineering techniques to create meaningful features that enhance model performance.
- Train models using appropriate algorithms and techniques, optimizing for accuracy and efficiency.
Collaborate with cross-functional teams to gather requirements and deliver solutions:
- Work closely with stakeholders from different departments to understand their needs and objectives.
- Translate business requirements into technical specifications for AI/ML solutions.
- Deliver tailored solutions that address specific challenges and add value to the organization.
Debug and troubleshoot AI/ML models and applications:
- Identify and resolve issues related to model performance, such as overfitting or underfitting.
- Debug application code to ensure smooth integration and functionality of AI/ML models.
- Perform root cause analysis to address any anomalies or errors in the models and applications.
Participate in code reviews and contribute to team success:
- Engage in regular code reviews to ensure code quality and adherence to best practices.
- Provide constructive feedback to peers and incorporate suggestions to improve your own code.
- Collaborate with team members to achieve project milestones and contribute to the overall success of the team.
Ensure compliance with coding standards and best practices:
- Write clean, maintainable, and well-documented code that follows industry standards.
- Stay updated with the latest coding practices and integrate them into your work.
- Conduct peer reviews to maintain high standards of code quality and consistency.
Continuously improve technical skills and knowledge:
- Engage in continuous learning through online courses, workshops, and reading relevant literature.
- Experiment with new tools and technologies to understand their potential applications. Attend conferences, webinars, and meetups to network with professionals and learn from experts.
Responsibilities
Job Complexity & Problem Solving
- Continuously develop technical skills to keep up with technology advancements.
- Ability to debug and troubleshoot complex AI/ML models.
Leadership & Stakeholder Management
- Ability to develop and maintain high-quality AI/ML models.
- Strong problem-solving and debugging skills.
- Ability to work collaboratively in a team environment.
Technical Competencies
- Working knowledge for cloud development (Containerization, Cloud Services (AWS, Azure), API Design, Microservice Architecture)
- Ability to deploy AI models into production effectively and at scale.
- Strong understanding in LLM techniques, for ex: tokenization, RAG, Reinforcement Learning and etc.
- Experience with data preprocessing, feature engineering, and model training.
- Capability to stay abreast of new research and integrate the latest advancements.
- Academic Qualifications: At least a Bachelor’s degree in Computer Science, Data Science, or a related field.
- Minimum of 2 years of experience in AI/ML development.
- Proficiency in programming languages such as Python/Java.
- Strong problem-solving and debugging skills.
- Ability to work collaboratively in a team environment.
Skills Required
- Bachelor’s degree in Computer Science, Data Science, or a related field
- At least 2 years of experience in AI/ML development
- Proficiency in Python or Java
- Strong problem-solving and debugging skills
- Ability to work collaboratively in a team environment
- Working knowledge of cloud development, including containerization and AWS or Azure
- Knowledge of API design and microservice architecture
- Ability to deploy AI models into production effectively and at scale
- Understanding of LLM techniques, including tokenization, RAG, and reinforcement learning
- Experience with data preprocessing, feature engineering, and model training
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The Company
What We Do
Bank Negara Malaysia is Malaysia’s central bank, mandated to promote monetary and financial stability conducive to sustainable economic growth. It maintains price stability, supports financial-system resilience, develops financial infrastructure and inclusion, oversees efficient and secure payment systems, advises the government on macroeconomic policy and public debt, issues the national currency, and manages Malaysia’s international reserves through its national central-banking responsibilities.
