Machine Learning Ops Lead - VP
On-site · Singapore, Singapore
Job Summary
Lead the design, build, and maintenance of end‐to‐end MLOps and LLMOps pipelines. Drive CI/CD automation, containerization, and deployment of AI models on AWS (SageMaker) with Kubernetes orchestration. Mentor engineers, collaborate with data scientists, ensure security/compliance of ML pipelines, and contribute to architectural roadmaps. Requires a degree in CS/SE/Data Eng or related field and 5+ years in MLOps/DevOps with leadership experience; strong Python and cloud-native tooling skills; experience with MLflow/Kubeflow/SageMaker Pipelines; excellent communication and collaboration skills.
Required Qualifications
- A degree in Computer Science, Software Engineering, Data Engineering, or a related field.
- 5+ years of experience in MLOps, DevOps, or cloud-native engineering.
- At least 2+ years in a leadership role.
- Proficiency in Python and model inferencing stack (Ray, VLLM, SGLang).
- Hands-on experience with Docker and Kubernetes (EKS).
- Expert knowledge of AWS services (SageMaker, ECR/ECS/EKS, Lambda, S3, CloudWatch, IAM, CloudFormation/Terraform).
- Strong CI/CD tooling and infrastructure-as-code principles.
- Experience with ML lifecycle tools (MLflow, Kubeflow, or SageMaker Pipelines).
- Excellent communication and mentorship abilities.
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