Senior Machine Learning Engineer

Job Description

Your 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. Core Responsibilities: • 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 Your skills & Your Experience Required Skills & Experience: 7-10 years of experience in ML Engineering/MLOps Expert-level Python programming skills Strong experience with AWS services and cloud architecture Proficiency in shell scripting and automation Experience with API development frameworks Knowledge of ML frameworks and tools Understanding of DevOps practices Technical Competencies: Advanced proficiency in IT Risk Assessment & Management 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 Judgement 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 Your Qualifications Essential: • A degree in Engineering / Computer Science or a related discipline • Minimum 3 years of Experience in IT Industry, with hands on experience in ML Models development & Its maintenance & Data Science. Desirable: • Specialties: Big Data, CI/CD, AWS /Cloud Services. • Experience in Development (Coding, Testing) • Additional industry or product certification Your Development If you live the values and demonstrate the people capabilities, we can offer great opportunities. Whether you want to move across the organisation or up into a leadership role, the ways you live the values and demonstrate the people capabilities are key to progressing. From this role, you could transition into other roles to broaden your technology coverage as part of developing yourself for more senior role either in same portfolio or different portfolio. Use the people and enterprise services capabilities required for this role as a guide to the critical skills and behaviours you need for your next move. Proficient in FastAPI, MLOps, and Python. API Development & Integration: Develop RESTful APIs using Django, Langchain and Node.js; Create efficient data processing pipelines; Implement MLOps best practices Strong background in machine learning and data science. Experience with building and implementing data models and algorithms. Testing and validating models. Familiarity with AWS SageMaker. Preferences: Candidates with a background in statistics and mathematics may not be a good fit. Not primarily looking for GCP expertise. AI Ops experience is not a priority but acceptable. Certification: Any associate-level cloud certification is acceptable. Open for candidates with 60-90days notice period. Note: Require 100% Diversity profiles .