AI Engineer

RHB Bank; Kuala Lumpur; On-site; MYR 80,000 - 120,000; Full time

Job summary

A leading financial institution in Kuala Lumpur is seeking an AI Engineer to develop and optimize AI-driven solutions. The role requires collaboration with product teams and expertise in AI and machine learning development, focusing on deploying models into production environments. Candidates should have experience with Python, cloud platforms, and AI frameworks. This position offers opportunities for career growth and exposure to cutting-edge technologies.

Benefits

Career growth opportunities

Exposure to advanced AI technologies

Qualifications

• 2-3 years of hands-on experience in AI and machine learning development.
• Strong proficiency in programming languages like Python.
• In-depth understanding of AI models and machine learning techniques.

Responsibilities

• Collaborate with product owners to understand business requirements.
• Engineer system prompts and integrate API calls to AI services.
• Optimize AI systems and models for accuracy and reliability.

Skills

AI and machine learning development

Programming in Python

Data preprocessing

Feature engineering

Cloud platforms (AWS, Azure)

Knowledge of NLP

Hyperparameter tuning

Containerization (Docker, Kubernetes)

Team collaboration (Agile)

Education

Bachelor's degree in AI, Data Science, or related field

Tools

Azure Machine Learning

AWS SageMaker

Azure AI Studio

Job description

Responsibilities

• Collaborate with product owners and domain experts to understand business requirements and tailor AI solutions accordingly.
• Work closely with Data Scientists/Cloud Platform teams to deploy models seamlessly into production environments.
• Optimize AI systems and models to ensure high levels of accuracy and reliability.
• Engineer system prompts and integrate API calls to generative AI services (Azure OpenAI, AWS Bedrock) to deliver sophisticated AI-driven solutions.
• Design and develop advanced GenAI models and algorithms to solve complex business problems within the financial sector.
• Train, fine-tune, and validate AI models to ensure high levels of accuracy and reliability.
• Optimize machine learning models and ensure they integrate effectively with existing systems.
• Develop end-to-end GenAI project lifecycle, including data preprocessing, model training, deployment, and continuous improvement.
• Perform hyperparameter tuning, algorithm selection, and feature engineering to optimize model performance. Troubleshoot and resolve issues related to AI models and implementations.
• Ensure compliance with financial services industry (FSI) standards, ethical AI practices, and implement AI governance and AI security safeguards.
• Create and maintain documentation for AI models and their applications.
• Research and stay up-to-date on the latest advancements in AI technologies and methodologies.

Qualifications

• Minimum Bachelor\'s degree in AI, Data Science, Computer Science, or a related field.
• Minimum of 2-3 years of hands-on experience in AI and machine learning development.
• Strong proficiency in programming languages like Python and experience with AI frameworks.
• In-depth understanding of AI models, machine learning, natural language processing (NLP), deep learning architectures, and statistical models.
• Solid knowledge of cloud platforms (AWS, Azure) and experience deploying AI models in production environments.
• Experience in architecting and implementing large-scale AI solutions aligned with business goals.
• Expertise in data preprocessing, feature engineering, model training, and hyperparameter tuning.
• Experience in training, testing, and prompt engineering technique.
• Experience with containerization and orchestration technologies such as Docker or Kubernetes, particularly for AI model deployment.
• Hands-on experience with cloud-based studio tools like Azure Machine Learning, Azure AI Studio, AWS SageMaker.
• Strong problem-solving skills, with a focus on optimizing AI model performance and scalability.

Other Skills

• A background of working with development and DevOps/DevSecOps best practices.
• Work iteratively in a team (Agile ways of working) with continuous collaboration.
• Self-motivated and strong communication.
• Ability to lead and influence team members.
• Problem management and analytical thinking.

Benefits / Career Growth

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