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.