AI-Driven DevOps & MLOps Engineer

Leaders; Sydney; On-site; AUD 140,000 - 200,000; Full time

Job summary

Leaders is seeking a Data Science & DevOps Engineer to join a multidisciplinary team and help shape how AI and data science capabilities move from experimentation through to production and operational use.

Lead engineering approaches for AI, ML and data science solutions, and design AWS-based architectures that productionize prototypes while building reusable patterns for pipelines, monitoring, and secure integration across teams.

Qualifications

• Experience delivering AI/ML solutions end-to-end.
• Strong AWS platform expertise.
• Technical leadership across ML Engineering, DevOps and Data Engineering.
• Ability to move 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, data pipelines, monitoring and secure integration.
• Champion DevOps, MLOps, testing, version control, automation and reproducibility.
• Lead and coordinate across ML Engineering, DevOps and Data Engineering.
• Work with Lead Data Scientists to translate analytical models into scalable implementations.
• Help establish technical standards and reusable engineering assets.
• Collaborate with security, privacy and data governance teams for production deployment.

Skills

AWS

AI/ML engineering

DevOps

Data engineering

Technical leadership

Tools

Git

CI/CD

Job description

Leaders is seeking a Data Science & DevOps Engineer to join a multidisciplinary team and help shape how AI and data science capabilities move from experimentation through to production and operational use.

Lead engineering approaches for AI, ML and data science solutions, and design AWS-based architectures that productionize prototypes while building reusable patterns for pipelines, monitoring, and secure integration across teams.