Job Description

JOB DUTIES AND RESPONSIBILITIES

Deploy & Monitor ML Models: Manage the deployment of LLM and chatbot models using Kubernetes, Docker, and cloud-native tools across AWS or GCP. Model Orchestration: Implement ML pipelines using Airflow, Kubeflow, or MLFlow for training, serving, and monitoring workflows. CI/CD for ML Workflows: Set up Git-based CI/CD pipelines using Jenkins or similar tools to ensure reliable deployments and rollbacks. Observability & Monitoring: Implement logging, tracing, and performance monitoring stacks (e.g., Grafana, Prometheus, ELK). Cost Optimization: Continuously optimize resource utilization, scaling strategies, and deployment costs across cloud environments. API & Traffic Management: Configure API gateways (Kong) and load balancing solutions (Kafka, Zookeeper) to ensure reliable and secure model serving. Automation & Scripting: Develop automation scripts and operational dashboards for model health, inference latency, and error tracking. Microservices Architecture: Design and manage microservices-based ML systems for modular, scalable deployments. Data Management: Ensure integration with Postgres DB for metadata storage, logs, and system configuration.

JOB REQUIREMENTS

Education

Bachelor's degree in Computer Science, Data Engineering, AI/ML, or related fields.
Experience

1 - 3 years of experience in MLOps, DevOps, or Cloud Engineering with ML-focused workflows. Experience working with LLM-based ML models is preferred but not mandatory.
Technical Skills

Cloud & OS: AWS, GCP, Ubuntu/Linux administration. Containerization & Orchestration: Kubernetes, Docker, MLFlow, Kubeflow, Airflow. CI/CD & Version Control: Git, GitHub Actions, Jenkins, GitLab CI/CD. Monitoring & Observability: Grafana, Prometheus, ELK stack. API & Traffic Management: API Gateways (Kong), Load Balancing (Kafka, Zookeeper). Databases & Data Ops: PostgreSQL database integration for ML pipelines. Architecture & Automation: Microservices architecture, Python, Bash scripting, YAML configurations.
Job Types: Full-time, Permanent

Pay: RM3,000.00 - RM5,500.00 per month

Benefits:

Health insurance Opportunities for promotion Professional development
Experience:

MLOps Engineer: 1 year (Preferred)
Work Location: In person