You are an experienced
MLOps Engineer
who is passionate about
machine learning platforms, automation, and cloud-native AI solutions
.
We're looking to set the standard for a
world-class, self-service, secure, and scalable MLOps platform
that enables rapid experimentation and safe production deployment of ML and Generative AI models.
Together, we can build
state-of-the-art AI and LLM platforms
that drive seamless, responsible experiences for millions of customers.
Do work that matters
Retail Banking Services (RBS) is the public face of CommBank, delivering a seamless banking experience for the future to our
10 million+ personal and small business customers
. We offer market-leading products and services, supported by some of the world's best systems, platforms, and engineering practices.
As a
Senior MLOps Engineer
, you will apply modern engineering and MLOps practices to operationalise machine learning and Large Language Models (LLMs) at scale. The role provides a strong chance to contribute to
AI platform uplift
,
cloud adoption
, and
enterprise-grade ML enablement
on AWS.
See yourself in our team
The
RBS Customer Remediation crew
is responsible for identifying root causes of issues, implementing control mitigations with Lines of Business, and ensuring customers are fully refunded for any bank error. We work closely with
Group Customer Advocacy & Remediation (GCAR)
,
Internal Audit
, and
Risk partners
to deliver fair and positive outcomes for customers.
As part of this crew, the Senior MLOps Engineer will enable reliable, compliant, and observable ML solutions that support remediation analytics, automation, and decisioning use cases.
Your responsibilities will include:
Design, build, and maintain end-to-end MLOps pipelines for training, testing, deployment, and monitoring of ML and LLM models.
Operationalise models using
AWS SageMaker
, including training jobs, pipelines, model registry, batch inference,



and real-time endpoints.
Support
LLM and Generative AI workloads
, including fine-tuning, inference optimisation, and deployment patterns.
Develop and maintain
CI/CD pipelines
for ML workflows and platform components.
Implement
monitoring and observability
for models and pipelines (data drift, model performance, system health).
Automate and improve ML development, release, and operational processes.
Take ownership of
production support and technical troubleshooting
for ML platforms and services.
Drive continuous improvement in
platform reliability, security, cost, and performance
.
Collaborate with data scientists and engineers to build robust ML pipelines that can
handle large datasets and traffic
.
Maintain
security adherence and compliance standards
, including data privacy and model explainability.
Ensure clear and
comprehensive documentation of MLOps processes
, infrastructure, along with configurations.
Participate as a senior member of the engineering team with minimal supervision and strong ownership and provide mentoring and technical assistance to other members of the team.
We're interested in hearing from people who:
Have hands-on experience operationalising machine learning models in a cloud environment (AWS preferred).
Are passionate about
MLOps, Cloud Engineering, Automation, and AI platforms
.
Enjoy solving complex problems using a structured, engineering-led approach.
Have strong experience with
Python
and familiarity with
SQL
for data analysis and validation.
Are comfortable working in
regulated,



large-scale enterprise environments
.
Technical Skills
We use a broad range of tools, languages, and frameworks. We don't expect you to know them all, but experience with some of the following (or equivalents) will set you up for success:
Strong experience with
AWS
, particularly
Amazon SageMaker
Experience with
Infrastructure as Code
(CloudFormation or Terraform)
Hands-on experience with core AWS services such as::S3, ECR, ECS, CloudWatch, KMS, secrets manager, Aurora DB, security groups
Experience supporting
LLM or Generative AI workloads
in production environments.
Strong programming and automation skills using
Python
Experience with
Docker and containerised ML workload
Hands-on experience with
CI/CD tools
(e.g. Git, GitHub Actions, Jenkins, TeamCity, Octopus, Artifactory) and
Understanding of
DevOps and MLOps best practices
including logging, monitoring, security, and reliability
Working with us
Whether you're passionate about customer service, driven by data, or called by creativity, a career with CommBank is for you.
We support our people with the flexibility to balance where work is done with at least half your time each month connecting in our Sydney or Melbourne office. We also have many other flexible working options available including changing start and finish times, part time arrangements and job share to name a few.
If this sounds like you, apply now!
If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We're keen to support you with the next step in your career.
We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on ************.
Advertising End Date: 28/05/2026

📌 Senior Software Engineer - Mlops (Sydney)
🏢 Commonwealth Bank Of Australia
📍 Sydney