Senior MLOps Engineer

📋 Description

• Provide technical leadership: Serve as the key technical SME for data scientists and ML engineers
• Own the experimental lifecycle: Architect and support the transition from data science
• Systematize ML delivery: Set shared patterns for how models are deployed, versioned, and released
• Establish closed-loop experimentation: Build a clear line of sight from live model telemetry back
• Reduce cost and remediate risk: Keep ML infrastructure and model-serving costs appropriate through
• Share knowledge and contribute: Help engineers grow through hands-on technical guidance, pairing

🎯 Requirements

• Strong familiarity with building, shipping, and maintaining robust machine learning systems on AWS
• 5+ years of experience across MLOps, DevOps, or Software Engineering, combining a strong
• Sound knowledge of industry-standard MLOps tooling, modern CI/CD practices, model registries, and
• Proven track record of building event-driven or distributed systems, applying appropriate
• A proactive approach to cloud cost optimization, infrastructure security, and access management

🎁 Benefits

• A place where you can move your career forward, where you'll be continuously backed to make new
• We're proud to be recognised as one of Australia's Best Workplaces™ by Great Place to Work®, a
• The support of a highly engaged, high-performing team including a leadership team that you'll
• 24 weeks paid parental leave for primary caregivers, four weeks paid secondary caregivers leave and