Platform and Capability Lead - ML
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About the role
The Platform and Capability Lead – ML is a key technical and commercial leadership position responsible for AGL’s end-to-end machine learning operations and platform capabilities. This role oversees the tools, processes, and infrastructure that enable the reliable and scalable development, deployment, monitoring, and maintenance of production ML models. Leading a small team of ML and MLOps Engineers, you will drive the industrialisation of AI/ML, accelerate time to production, and ensure strong governance and cost management across the platform.
What You’ll Be Doing
Owning AGL’s AI/MLOps frameworks, shared AI/ML platform services, model lifecycle governance, and platform reliability KPIs.
Defining and refining the roadmap for AI/MLOps and AI/ML platform capabilities aligned to organisational strategy.
Operating the AI/ML platform as a service, including SLO/SLA management, incident/problem/change processes, and continuous improvement.
Providing technical leadership and standards across workflow orchestration, feature stores, model registries, CI/CD, observability, and monitoring.
Implementing the AI/MLOps operating model across the full ML lifecycle to ensure repeatable, auditable, and scalable practices.
Managing platform FinOps, including budget control, capacity planning, cost optimisation, and tracking efficiencies in emerging technologies.
Leading and developing a high performing team of Machine Learning and MLOps Engineers with clear goals, coaching, and quality oversight.
What You’ll Bring
- Demonstrated experience in AI/MLOps, Machine Learning Engineering, or similar roles focused on deploying and scaling machine learning solutions in production.
Strong technical expertise in modern AI/ML architectures, deployment patterns, and operational best practices.
Hands on experience with AI/MLOps tooling such as MCP, Langchain, APIM, MLflow, , and cloud native AI/ML stacks (Azure preferred).
Solid understanding of containerisation, orchestration, microservices, software engineering, DevOps, and agile delivery.
Ability to influence and collaborate across data science, engineering, cyber, architecture, and product teams.
We’d love to see your application by Friday 13 February 2026.
At AGL, we offer a wide range of benefits including:
Flexible working: AGL offers a range of flexible working options including hybrid working and/or flexible hours.
Staff discounts: Discounted energy, telco and solar plans: Available for employees, family and friends.
Parental Leave: 20 weeks paid leave for the primary carer plus employer-paid superannuation on unpaid leave.
Additional Leave: 1 week ‘Recharge Leave’ for eligible employees and salary sacrifice up to 6 weeks additional leave.
Wellbeing Programs: Partnerships with Medibank and Fitness Passport and on-site health appointments (massage, skin checks etc.).
AGL Shares: Up to $1000 as part of annual Share Reward plan and salary sacrifice up to $5000 of shares.
*Benefits may change over time and vary based on role type and location.
Inclusion at AGL
At AGL, we value diversity and welcome applicants from various backgrounds, including Aboriginal and/or Torres Strait Islander peoples, individuals with disabilities, culturally diverse individuals, and members of the LGBTQ+ community. AGL is dedicated to maintaining a diverse workforce and encourages applicants to share their lived experiences.
We offer reasonable adjustments throughout the recruitment process and respect the privacy of those who choose not to disclose. To learn more visit: www.agl.com.au/careers
AGL is proud to be a WORK180 Endorsed Employer for All Women.
Our pre-employment screening process includes a Nationally Coordinated Criminal History Check and a medical assessment if necessary.
The information provided as part of your application to AGL will be managed in accordance with the AGL Privacy Policy.
AGL does not accept agency submissions unless approval has been granted by a member of the Talent Acquisition team. Candidates submitted by an agency without approval will not be considered by AGL.