Exciting opportunity with a rapidly growing AI-driven healthcare analytics company as an MLOps Engineer who will bridge the gap between data science and production engineering. You'll build and maintain the infrastructure that enables data scientists to ship models faster, more reliably, and at scale — across Singapore and across Asia.

Role

• Build and maintain ML pipelines and CI/CD workflows for model training, evaluation and deployment
• Manage model registries, versioning and experiment tracking (MLflow, Weights & Biases)
• Set up monitoring for model drift, data quality and system performance in production
• Containerise and orchestrate ML workloads using Docker, Kubernetes and cloud-native tools
• Collaborate with data scientists to translate prototypes into maintainable, production-ready systems

Responsibilities

• 3+ years in a DevOps, platform engineering or MLOps role
• Hands-on experience with ML pipeline tooling: Kubeflow, MLflow, Metaflow or similar
• Proficiency in Python and infrastructure-as-code (Terraform, Helm)
• Cloud platform experience: AWS, GCP or Azure — ML services a strong plus
• Solid understanding of the full ML lifecycle from data ingestion to model serving

Interested applicants, please submit your profile to submitCV@talentreq.com for review. We will be in touch for initial discussion upon being shortlisted

EA Licence: 17S8795 | EAP: R1108333