What you'll doBuild and maintain robust ML pipelines for model training, deployment, and monitoring.Collaborate with data scientists and stakeholders to understand business problems and translate them into machine learning solutions.Ensure data quality and pre-process complex datasets for model consumption, including feature engineering and selection.Stay up-to-date with the latest advancements in AI/ML, particularly within GCP, and propose new solutions to drive innovation.Provide guidance and mentorship to junior team members.What experience you needBS degree in a STEM major or equivalent discipline.5+ years of experience in machine learning engineering or related experienceProficiency in Python and SQL, including experience with relevant ML frameworksIntermediate understanding of GCP, especially services like Vertex AI, Dataflow, and Composer.Proven experience in the end-to-end lifecycle of building and deploying machine learning models.Experience with CI/CD integration for automated model deployment.Demonstrated ability to drive project success through effective stakeholder communication and management.Solid understanding of statistical analysis and machine learning algorithms.What could set you apartGCP Professional Machine Learning Engineer Certification.Deep knowledge of cloud security and compliance for ML workloads.Hands-on experience with Dataflow, Composer, Vertex AI, and API development for model serving.Expertise in MLOps (Machine Learning Operations) best practices.Experience with advanced ML techniques, such as deep learning or reinforcement learning.Primary Location: AUS-MelbourneAUS-Sydney-Blue-StreetFunction: Function - Data and AnalyticsSchedule: Full time
