DevSecOps / ML Ops Engineer

DevSecOps / MLOps Engineer

Employment Type:

Contract (1 year)

Seniority:

Senior Consultant (Level 3)

Start Date:

September 2026

Industry:

Government / Public Sector Technology

About the Role:

We are seeking a senior DevSecOps Engineer to operationalize ML models into production, manage platform security and compliance, and ensure data quality across a national-scale robotics platform. You will work at the intersection of MLOps, security, and cloud infrastructure, with knowledge transfer to the internal team as a core requirement.

Key Responsibilities:

Own the operationalization and deployment of ML models into production.

Manage ML infrastructure and monitor model performance, ensuring reliability and accuracy over time.

Own platform security and compliance:

IM8 compliance, Government Commercial Cloud (GCC) security baseline , and other applicable data compliance requirements.

Address data privacy requirements (e.g., PDPA), including PII redaction/blurring in sensitive data sources (e.g., CCTV feeds).

Manage configuration, deployment, and operational readiness of the data platform on

GCC .

Implement infrastructure security controls meeting GCC security baselines.

Own data quality standards: completeness, accuracy, schema conformance, and latency compliance.

Produce infrastructure runbooks covering deployment, configuration, and troubleshooting.

Progressively transfer MLOps, security, compliance, and data quality knowledge to the internal team.

Requirements:

Degree in Computer Science, Engineering, Information Security, or related field.

8+ years

of experience in ML Ops, security engineering, or compliance for cloud platforms.

Proven experience operationalizing and deploying ML models in production, including model monitoring and performance management.

Hands-on experience with government or public-sector security compliance frameworks ; cloud security experience on

AWS preferred .

Experience implementing data privacy controls such as PII redaction and blurring.

Must have served as lead security or MLOps engineer for the majority duration

of national or large-scale, high-sensitivity government/public-sector platforms.

Extensive hands-on experience operating

AWS cloud infrastructure .

Experience deploying and operating data platforms (e.g.,

Databricks or comparable ) in cloud or government-compliant environments, from build through production monitoring and incident response.

Strong understanding of data quality dimensions and building automated validation checks within pipelines.

Demonstrated experience delivering comparable data platform projects internationally at city-level or above , beyond Singapore.

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