ML Ops Engineer

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. office.com

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

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
Visit us at www.accenture.com

Equal Employment Opportunity Statement

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.