Senior AI/ML DevOps Engineer - AWS Production Pipelines

Peoplebank; Sydney; On-site; AUD 120,000 - 150,000; Full time

Job summary

Peoplebank is seeking a Data Science & DevOps Engineer to join a multidisciplinary team and drive AI capabilities from experimentation through to production. You will lead ML engineering, DevOps, and data engineering initiatives across AWS, ML pipelines, and secure integration.

Work with cyber security, data governance, and operations teams to ship scalable, reusable patterns for model serving, monitoring, and automation.

Qualifications

• Experience delivering AI/ML solutions on AWS
• Ability to move prototypes/PoCs through to production
• Leadership across ML Engineering, DevOps and Data Engineering
• Experience with data pipelines, monitoring and reproducibility

Responsibilities

• Lead engineering approaches for AI, ML and data science solutions
• Design and implement AWS-based AI and data science solutions
• Establish pathways for prototypes and PoCs to reach production readiness
• Develop reusable patterns for model serving, RAG, document intelligence, data pipelines, monitoring and secure integration
• Champion DevOps, MLOps, testing, version control, automation and reproducibility
• Lead and coordinate specialists across ML Engineering, DevOps and Data Engineering
• Work closely with Lead Data Scientists to translate analytical models into robust, scalable implementations
• Help establish technical standards, guides and reusable engineering assets
• Work across technology, cyber security, privacy, data governance and operational teams to support production deployment

Skills

Technical leadership

Cross-functional collaboration

Production deployment

AI/ML engineering

Tools

AWS

CI/CD pipelines

Job description

Peoplebank is seeking a Data Science & DevOps Engineer to join a multidisciplinary team and drive AI capabilities from experimentation through to production. You will lead ML engineering, DevOps, and data engineering initiatives across AWS, ML pipelines, and secure integration.

Work with cyber security, data governance, and operations teams to ship scalable, reusable patterns for model serving, monitoring, and automation.