ML Ops Engineer
The ML Ops Engineer will design and deploy AI-driven risk assessment models for the Guardian/ITS platform within a secure government environment. Key responsibilities include model development, prototyping, MLOps alignment, and ensuring compliance with responsible AI and governance standards. The role involves close collaboration with architecture, data engineering, and platform teams to bridge the gap between analytical concepts and production outcomes. The position requires a focus on model reproducibility, monitoring, and operational readiness for high-stakes government applications.
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Experience
Experience not specified
Function
Engineering
Work mode
Onsite, Singapore
Company
Tier 2
What you will work on
The ML Ops Engineer will design and deploy AI-driven risk assessment models for the Guardian/ITS platform within a secure government environment. Key responsibilities include model development, prototyping, MLOps alignment, and ensuring compliance with responsible AI and governance standards. The role involves close collaboration with architecture, data engineering, and platform teams to bridge the gap between analytical concepts and production outcomes. The position requires a focus on model reproducibility, monitoring, and operational readiness for high-stakes government applications.
TAL's take
Solid role within a major consultancy focusing on government ML infrastructure, though lacks specific technical stack details.
Clear responsibilities and domain context, though the lack of a specific tech stack lowers the specificity slightly.
Must haves
- Experience in machine learning delivery and model validation
- Ability to perform feature engineering and experimentation
- Familiarity with production ML pathways and model versioning
- Experience with responsible AI principles and data governance
- Strong stakeholder and cross-functional collaboration skills
About the company
Global consultancy firm with significant government and enterprise tech engagements.
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