ML Ops Architect

TECH AALTO PTE. LTD.; Remote; SGD 60,000 - 80,000; Part time

Job summary

A technology firm in Singapore is seeking an experienced MLOps Architect with expertise in AWS SageMaker to provide high-level architectural guidance for an enterprise-grade MLOps platform. This role emphasizes design and integration advisory rather than hands-on development, working closely with engineering and compliance teams. The position allows for remote work, and part-time candidates are welcome. Ideal for individuals with strong skills in MLOps architecture, communication, and stakeholder engagement.

Qualifications

• Proven experience designing enterprise-grade MLOps platforms on AWS, especially with SageMaker.
• Strong architectural background in ML CI/CD, model registries, feature stores, monitoring, and orchestration.
• Experience in regulated industries.
• Excellent communication skills to articulate architectural tradeoffs.

Responsibilities

• Provide high-level architecture design for AWS-based MLOps ecosystem.
• Advise on component boundaries and integration points.
• Review CI/CD best practices for ML workflows.
• Ensure architectural recommendations align with compliance requirements.
• Support architectural decisions with platform engineering teams.
• Offer guidance on operationalizing ML in regulated environments.

Skills

Enterprise-grade MLOps platforms design

AWS SageMaker

ML CI/CD

Model registries

Feature stores

Monitoring & observability

ML pipeline orchestration

Communication skills

Stakeholder engagement

Consulting with compliance stakeholders

Job description

Job Description: MLOps Architect(AWS SageMaker)

About the Role

We are seeking an experienced MLOps Architect with deep expertise in AWS and SageMaker 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.

Required Skills & Capabilities

• Proven experience designing enterprise-grade MLOps platforms on AWS, especially with SageMaker 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.

Deliverables / Expectations

• 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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