Job Role:- MLOps Engineer

Job Location:- Singapore

Experience:- 8+ Years

Roles & Responsibilities:-

• Design, build, and maintain scalable MLOps pipelines to support machine learning model development, deployment, and monitoring.
• Develop and manage data pipelines and infrastructure for data science, analytics, and AI/ML workloads.
• Collaborate with data scientists and engineering teams to validate use cases, test hypotheses, and operationalise machine learning solutions.
• Automate model training, deployment, versioning, monitoring, and lifecycle management using MLOps best practices.
• Ensure data pipelines and platform architecture support scalable, reliable, and reproducible ML workflows.
• Monitor ML models and data pipelines to optimise performance, reliability, and operational efficiency.
• Implement CI/CD practices, automation, and infrastructure-as-code for ML environments.
• Prepare technical documentation and support knowledge transfer to internal teams.

Skills & Requirements:-

• Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related discipline.
• Minimum 8 years of experience in MLOps, Machine Learning Engineering, Data Engineering, or Data Science.
• Proven experience building, deploying, and maintaining machine learning pipelines in cloud environments.
• Strong understanding of MLOps practices, model lifecycle management, CI/CD, and workflow automation.
• Experience working with data scientists to develop, validate, and deploy machine learning solutions.
• Familiarity with enterprise data platform architectures supporting AI/ML workloads.
• Proficiency in Python, SQL, and cloud-native data and ML services is preferred.
• Strong analytical, problem-solving, collaboration, and communication skills.