Roles & Responsibilities:
As a Senior ML Engineer, You will be expected to perform the following tasks and responsibilities in a manner consistent with CBA's Values and People Capabilities.
- AI/ML Strategy Implementation: Support CDO in executing the Group's AI strategy; Drive E2E AI use cases with cutting-edge technologies; Align solutions with Group's data strategy and architecture
- ML Platform Development: Design and implement scalable ML platforms; Build automated ML pipelines using Python and AWS services; Ensure robust model deployment and monitoring systems
- Cloud Infrastructure Management: Utilize AWS services (CloudFormation/Terraform, S3, CloudWatch, IAM, EC2, ECR, Lambda, EMR, SageMaker); Implement infrastructure as code practices; Maintain security and compliance standards
- API Development & Integration: Develop RESTful APIs using Django, Langchain , and Node.js; Create efficient data processing pipelines; Implement MLOps best practices
- Technical Leadership: Provide technical guidance on ML infrastructure; Collaborate with data scientists and business stakeholders; Drive innovation in AI/ML technology adoption
- Risk: Operate within the CBA Group risk appetite and effectively manage strategic and operational risk related to data.
- Adhere to our Code of Conduct. The Code of Conduct sets the standards of behavior, actions and decisions we expect from our people.
- Agreements, SLOs (Service Level Objectives) and financial targets and results (Service Delivery Components) are achievable and adequate.
- Involvement in any audits of the services within your control and managing any subsequent follow-up activities.
Essential Skills:
- 7-10 years of experience in ML Engineering/MLOps with knowledge of ML frameworks and tools with hands on experience in ML Models development & It’s maintenance & Data Science
- Expert-level Python programming skills
- Strong experience with AWS services and cloud architecture with proficiency in shell scripting and automation
- Experience with API development frameworks and understanding of DevOps practices
- Advanced proficiency in IT Risk Assessment & Management and advanced Systems Management capabilities
- Sound consulting and critical analysis skills
- Strong negotiation and service partner management abilities
- People Capabilities: Customer Focus; Team and Culture building; Continuous Improvement mindset; Effective Communication; Strong Judgment; Results-Driven approach
- Good to Have: Basic understanding of database concepts, SQL; Domain experience in finance, banking, Insurance; Good understanding of AI/ML concepts and GenAI foundations
Education Qualifications:
- Bachelor’s degree/Master’s degree/Ph.D. in Data Science, Machine Learning, Computer Science, Computational Linguistics, Statistics, Mathematics, Physics
- Additional industry or product certification