Machine Learning/LLM Ops Engineer
CIMB Niaga
Indonesia | Banten
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Machine Learning/LLM Ops Engineer
CIMB Niaga (Kota Tangerang, Banten, Indonesia)
Banten,
Indonesia
CIMB Group is Malaysia’s second largest financial services provider and one of ASEAN’s leading universal banking groups. It offers consumer banking, investment banking, Islamic banking, asset management and insurance products and services. Headquartered in Kuala Lumpur, the Group is now present in 9 out of 10 ASEAN nations (Malaysia, Indonesia, Thailand, Singapore, Cambodia, Brunei, Vietnam, Myanmar and Laos). Beyond ASEAN, the Group has market presence in China, Hong Kong, Bahrain, India, Sri Lanka, Taiwan, the US, UK and Korea. CIMB Group is listed on the Malaysian stock exchange via CIMB Group Holdings Berhad. As at 30 June 2015, the Group had a market capitalization of USD46.4 billion and about 44,000 employees located in 17 countries.
About this position
The ML/LLM Ops Engineer is specialized in AI industrialization and is tasked with managing the operational aspects of machine learning and deep learning models within the Bank's AI industrialization framework.
Responsibilities
Key Responsibilities:
• Setup, configuring and manage the productions infrastructure (i.e. configure GPU, Batch size, security, and set othe parameters or software require) to ensure optimal resource allocation for model training and inference.
• Implement best practices for version control, model reproducibility and implement governance.
• Resource management, model performance, model versioning, and infrastructure.
• Create and maintain documentation for model architecture, deployment processes, and operational procedures.
• Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes.
• Design, develop, and implement MLOps pipelines for the continuous deployment and integration of machine learning models.
• Develop and maintain CI/CD pipelines for data and machine learning models.
• Use tools like Docker to containerize models for easier deployment across different environments.
• Ensure compliance with security and data privacy standards in all MLOps activities.
• Automate the training, testing and deployment processes for machine learning models.
• Setting up monitoring for the ML pipeline and automated model retraining.
• Continuously monitor and maintain models in production, ensuring optimal computational performance, accuracy and reliability (anomalies or degradation of the model quality) by Collecting data about the model performance on live data.
• Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
• Continuous improvement by establish feedback mechanisms to gather insights from model performance and user interactions.
• Troubleshoot and resolve issues related to model deployment and performance.
• Keep up-to-date with the latest MLOps tools, technologies and trends.
• Provide support and guidance to other team members on MLOps practices.
• Ensure compliance as regulated in CIMB Niaga.
Requirements
Qualifications:
• Bachelor’s degree in Computer Science, Computer Engineering, or relevant field.
• At least 5 to 7 years of experience as Data Scientist, Data Engineer and MLOps (machine learning or deep learning operations).
• Technical skills: CI/CD cycle (orchestrated by GitLab CI, GitHub Actions, Circle CI, or similar tools), DevOps pipeline.
About CIMB Niaga
CIMB Group is Malaysia’s second largest financial services provider and one of ASEAN’s leading universal banking groups. It offers consumer banking, investment banking, Islamic banking, asset management and insurance products and services. Headquartered in Kuala Lumpur, the Group is now present in 9 out of 10 ASEAN nations (Malaysia, Indonesia, Thailand, Singapore, Cambodia, Brunei, Vietnam, Myanmar and Laos). Beyond ASEAN, the Group has market presence in China, Hong Kong, Bahrain, India, Sri Lanka, Taiwan, the US, UK and Korea. CIMB Group is listed on the Malaysian stock exchange via CIMB Group Holdings Berhad. As at 30 June 2015, the Group had a market capitalization of USD46.4 billion and about 44,000 employees located in 17 countries.