Ml Ops

**Responsibilities**:

- Implement and optimize continuous integration/continuous deployment (CI/CD) pipelines for machine learning models
- Collaborate with DevOps and IT teams to integrate machine learning workflows with existing systems and infrastructure
- Develop the engineering architecture and data pipelines needed to enable large-scale machine learning systems
- Work with stakeholders across the organization to understand their machine learning needs and requirements, and to develop MLOps solutions that meet those needs
- Implement best practices for version control, model versioning, and reproducibility in machine learning projects

**Requirements**:

- Bachelor's/Master's degree in Computer Science, Artificial Intelligence, or a related field from reputable university
- 2-5 years of experience in MLOps, Machine Learning engineering, Data engineering, or a related field
- Solid understanding of ML model training concepts
- Experience with popular ML frameworks (TensorFlow, PyTorch, scikit-learn)
- Familiarity with model deployment tools (e.g., MLflow, TensorFlow Serving, Kubeflow)
- Proven experience deploying machine learning models into production environments
- Expertise in building and maintaining CI/CD pipelines for machine learning
- Strong knowledge of containerization and container orchestration technologies, such as Docker and Kubernetes
- Experience in any of the cloud platforms (Azure, Google Cloud, or AWS)
- Knowledge of using monitoring and logging tools (e.g., Prometheus)

**Salary**: Rp6,000,000 - Rp10,000,000 per month