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Staff Platform Engineer

1 month ago

Sydney, New South Wales, Australia Commonwealth Bank of Australia Full time
About the Role

We are seeking a highly experienced Staff Platform Engineer to join our team at the Commonwealth Bank of Australia. As a key member of our engineering team, you will be responsible for designing, building, and running tools, infrastructure, templates, and capabilities that our data science community and other engineers use to deliver business value.

Key Responsibilities

  • Provide strategic technical leadership and mentorship driving best practices for ML platform architecture, deployment, and scaling.
  • Oversee the design and development of scalable and resilient AI infrastructure with a focus on performance and reliability and architect core components, ensuring performance, reliability, and scalability.
  • Create a standardized set of tooling for deploying and running applications and setting them up with best practices.
  • Collaborate with customer-facing product owners and engineers to design, build, and run platforms that they can use to deliver customer value at greater quality, velocity, and safety.
  • Make all platforms entirely self-service, secure, and available within minutes without human approval.
  • Collaborate with data scientists, engineers, and stakeholders to define and implement technical requirements. Translate needs into technical solutions and ensure the platform's reliability through robust monitoring, logging, and alerting systems.
  • Develop and maintain comprehensive documentation, including architecture blueprints and best practices, as well as conduct workshops and training sessions to educate and align the team on platform usage and best practices.
  • Stay up to date with the latest developments in the field of ML, MLOps, LLMs, GPUs, and related concepts.
  • R&D on emerging AWS technology.

Requirements

  • Expertise in AWS services such as EC2, ECS, S3, Lambda, Step function, RDS, DynamoDB, IAM, VPC, Route 53, Cloudwatch, EKS.
  • Experience with the end-to-end ML lifecycle, including data preprocessing, feature engineering, model training, evaluation, and deployment.
  • Proficiency in automation and scripting (Bash, Python).
  • Hands-on experience with infrastructure as code tools like AWS CloudFormation.
  • Proficiency with version control systems like GitHub, GitHub Actions.
  • Expertise in tools like Grafana, Prometheus.
  • Artifactory, Synk, Docker.

What We Offer

We offer a dynamic and inclusive work environment, with opportunities for professional growth and development. We are committed to being an accessible employer and want to make finding your dream job as easy as possible. If you experience any accessibility issues or require additional support, please contact HR Direct.

We support our people with the flexibility to balance where work is done with at least half your time each month connecting in 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. Talk to us about how these arrangements might work for you.