ML Ops Architect
Singapore
Listed on 2025-12-14
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IT/Tech
Cloud Computing
Job Description: MLOps Architect(AWS Sage Maker)
About the Role
We are seeking an experienced MLOps Architect with deep expertise in AWS and Sage Maker to provide high-level architectural guidance and advisory support for an enterprise-grade MLOps platform. This role is focused on conceptual design, architecture reviews, and integration advisory rather than hands-on development.
You will work closely with platform engineering, data, and compliance teams to ensure the MLOps ecosystem is scalable, compliant, and aligned with best-practice enterprise standards.
Key Responsibilities- Provide high-level architecture design for the client's AWS-based MLOps ecosystem (training, inference, pipelines, registry, monitoring).
- Advise on component boundaries, integration points, and workflow design across the MLOps stack.
- Review and recommend best practices for CI/CD for ML workflows
, feature stores, model registries, and observability tooling. - Ensure architectural recommendations align with security, governance, and compliance requirements.
- Collaborate with platform engineering and data teams to support architectural decisions.
- Offer conceptual guidance and architecture-level support around operationalizing ML in regulated environments.
- Proven experience designing enterprise-grade MLOps platforms on AWS, especially with Sage Maker and the broader AWS AI ecosystem.
- Strong architectural background across:
- ML CI/CD
- Model registries
- Feature stores
- Monitoring & observability
- ML pipeline orchestration
- Experience working in regulated or compliance-heavy industries.
- Ability to engage and consult with platform engineering, data engineering, and compliance stakeholders.
- Excellent communication skills and ability to articulate architectural tradeoffs.
- High-Level MLOps Architecture Blueprint covering training, inference, pipelines, registry, monitoring, and governance.
- Advisory recommendations on component boundaries and architectural integration points.
- Guidance on compliance alignment for ML workflows in AWS.
- Ongoing support for conceptual and architecture-level questions throughout the engagement.
This role is for remote working and those who are looking for half day part time work are also welcome.
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