AI/ML DevOps Engineer - Production-Ready Pipelines

Leaders; Sydney; On-site; AUD 150,000 - 210,000; Full time

Job summary

Leaders IT invites an experienced Data Science & DevOps Engineer to join a multidisciplinary team, shaping AI capabilities from experimentation to production and operation. You will lead ML engineering, DevOps and data engineering efforts on AWS, delivering scalable, secure AI solutions.

You’ll build reusable patterns for model serving and data pipelines, drive automated testing, and collaborate across cyber security and governance teams to ensure robust deployments.

Qualifications

• Experience delivering AI/ML or data science solutions on AWS.
• Technical leadership of complex AI or data science projects.
• Experience moving prototypes/PoCs to production.

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

AI/ML engineering

AWS leadership

Data engineering

DevOps leadership

Cloud engineering

Cross-functional collaboration

Tools

AWS

Git

CI/CD pipelines

Monitoring & observability

Job description

Leaders IT invites an experienced Data Science & DevOps Engineer to join a multidisciplinary team, shaping AI capabilities from experimentation to production and operation. You will lead ML engineering, DevOps and data engineering efforts on AWS, delivering scalable, secure AI solutions.

You’ll build reusable patterns for model serving and data pipelines, drive automated testing, and collaborate across cyber security and governance teams to ensure robust deployments.