AI Engineer

RHB Banking Group; Selangor; On-site; MYR 70,000 - 90,000; Full time

Job summary

A leading banking institution is looking for an AI and Machine Learning Developer to create and optimize AI solutions tailored for the financial sector. Responsibilities include model deployment, collaboration with cross-functional teams, and ensuring compliance with industry standards. Ideal candidates should have a Bachelor's degree in a relevant field and experience with cloud platforms like AWS and Azure. This position is based in Selangor, Malaysia.

Qualifications

• Minimum of 2-3 years of hands-on experience in AI and machine learning development.
• Solid knowledge of cloud platforms like AWS and Azure.
• Experience in architecting and implementing large-scale AI solutions.

Responsibilities

• Collaborate with product owners to understand requirements.
• Deploy AI models into production environments.
• Optimize AI systems for accuracy and reliability.
• Develop and maintain documentation for AI models.

Skills

Python

AI frameworks

Machine learning

Natural language processing (NLP)

Deep learning architectures

Statistical models

Containerization (Docker)

Orchestration (Kubernetes)

Education

Bachelor's degree in AI, Data Science, Computer Science

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 Required

• 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.