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