A major bank in Sydney is seeking an ML Platform Engineer for a 12 month contract likely to extend.
As an ML Platform Engineer, you’ll play a vital role in designing, building, and maintaining the infrastructure and tools that drive the analytics teams to deliver business value at scale.
Key Skills:

• Design, implement, and maintain scalable and reliable ML infrastructure on AWS.
• Develop and support tools for the end-to-end ML lifecycle, including data ingestion, model deployment, and monitoring, with an emphasis on automation and DevSecOps.
• Work collaboratively with data scientists, engineers, and stakeholders to translate requirements into robust technical solutions.
• Build and maintain CI/CD pipelines to streamline ML model deployment and updates.
• Develop and maintain thorough platform documentation, including architecture blueprints and best practices.

Key Skills/ Experience:

• Hands-on experience with AWS services such as EC2, ECS, S3, Lambda, Step Functions, RDS, DynamoDB, IAM, VPC, Route 53, and CloudWatch.
• Experience with AWS ML services such as SageMaker, AWS Glue, Amazon EMR, and Airflow.
• Experience in building and scaling cloud infrastructure for machine learning use cases.
• Solid understanding of the ML lifecycle: data preprocessing, feature engineering, model training, evaluation, and deployment.
• Proficient scripting and automation skills in Bash and Python.
• Experience with Infrastructure-as-Code tools, especially AWS CloudFormation.
• Proficiency with version control systems such as GitHub and GitHub Actions.
• Familiarity with monitoring and observability tools like Grafana and Prometheus, as well as engineering tools such as Artifactory, Snyk, and Docker.
• Comfortable working across the full software lifecycle: design, build, change, and run.
• Strong communication skills and a commitment to inclusivity and continuous improvement.

If interested please respond ASAP