Accenture Southeast Asia Hiring! Full Time ML Ops Engineer in - Ricebowl

Role Purpose

Plays a critical role in delivering AI‑enabled risk assessment and decision support capabilities for the Guardian / ITS platform, translating analytical concepts into production‑ready, governable ML solutions within a high‑security government environment. [*************]

Key Responsibilities

Machine Learning Delivery

Design, develop, and validate ML models supporting risk scoring, profiling, and pattern detection.

Perform feature engineering, experimentation, and model evaluation on operational datasets.

Translate analytical hypotheses into deployable ML outcomes.

AI POC & Innovation

Contribute to AI Proof‑of‑Concept initiatives to validate feasibility, value, and scalability.

Rapidly prototype ML approaches and document findings, limitations, and recommendations.

Support transition of validated POCs toward production pathways.

Production & MLOps Alignment

Collaborate with engineering and platform teams to prepare models for controlled deployment.

Support model versioning, reproducibility, retraining considerations, and monitoring indicators.

Contribute to ML runbooks and operational readiness artefacts.

Architecture & Design Collaboration

Participate in solution architecture and design reviews from an ML perspective.

Ensure ML components align with system architecture, data contracts, and integration boundaries.

Advise on ML constraints, trade‑offs, and dependencies in system design decisions.

Responsible & Secure AI

Apply responsible AI principles including explainability, traceability, and bias awareness.

Ensure ML solutions comply with data protection, security, and governance requirements.

Support documentation required for audits, reviews, and regulatory assurance.

Stakeholder & Team Engagement

Provide clear updates on ML progress, risks, and outcomes to project stakeholders.

Collaborate cross‑functionally with data engineers, architects, and delivery leads.

Contribute to knowledge sharing and capability uplift within the ML / AI team.

Role Context

Embedded within the Machine Learning / AI team supporting Guardian / ITS.

Works closely with Architecture, Data Engineering, and Platform teams.

Direct contributor to the programme’s AI roadmap and delivery outcomes