3 days ago

MLOps Engineer

7-Eleven Australia

Melbourne

3 days ago

Apply

MLOps Engineer

7-Eleven Australia is seeking an MLOps Engineer to help the Data Science team deploy, operate and maintain machine learning and AI solutions in production. The role focuses on operationalising a strategic ML engine hosted in Databricks and supporting a growing portfolio of predictive modelling, optimisation and AI use cases. Requires strong Python, SQL and PySpark skills, plus experience with Azure Databricks, MLflow, Delta Lake, Unity Catalog and CI/CD practices.

Core AIHybridFull-timeSeniorPythonSQL

MLOps Engineer

Apply

Core AIHybridFull-timeSeniorPython

Salary

Not specified

Work Location

Melbourne, Victoria, Australia, AU

Work Model

Work Your Way. Enjoy the perfect balance of remote flexibility and in-office collaboration—get the best of both worlds

Employment Type

Full-time

Experience Level

Mid-Senior level

Core Qualifications

Technical (Must-have)

PythonSQLPySparkAzure DatabricksMLflowDelta LakeUnity CatalogDatabricks WorkflowsCI/CDAzure DevOpsUnit TestingIntegration TestingData Processing Performance OptimisationAI GovernanceAccess Controls

Soft Skills

CollaborationProblem SolvingCommunication

Preferred Qualifications

Technical (Nice-to-have)

Generative AILLM ApplicationsRAGVector SearchAgent Orchestration FrameworksAI Agent ManagementMCP OrchestrationAzure Cloud ServicesDatabricks Certifications

Key Responsibilities

•Partner with Data Science to take models from experimentation through validation, deployment and ongoing production management
•Implement and maintain production workflows for data ingestion and processing, model execution, retraining, testing and deployment
•Build and maintain CI/CD pipelines and controlled release processes for machine learning and AI workloads
•Build and maintain robust data and feature pipelines required by machine learning and AI solutions
•Diagnose production issues and work with Data Science and Engineers to resolve model, data and platform problems
•Implement appropriate access controls, security and governance within Databricks, including access and action permissions for AI agents and automated systems in line with enterprise standards
•Support operationalising of Generative AI solutions, including LLM applications, RAG and emerging AI use cases
•Contribute to reusable templates, tooling and MLOps practices that make it easier to deploy new models consistently
•Contribute to establishing best practice, configure and set up state of the art tooling to meet production standards
•Support performance optimisation and efficient use of Databricks and cloud infrastructure

MLOpsMachine LearningAIDatabricksAzureRetailEngineeringFull-timeMelbourneOn-site

Key Responsibilities

•Partner with Data Science to take models from experimentation through validation, deployment and ongoing production management

•Implement and maintain production workflows for data ingestion and processing, model execution, retraining, testing and deployment

•Build and maintain CI/CD pipelines and controlled release processes for machine learning and AI workloads

•Build and maintain robust data and feature pipelines required by machine learning and AI solutions

•Diagnose production issues and work with Data Science and Engineers to resolve model, data and platform problems

•Implement appropriate access controls, security and governance within Databricks, including access and action permissions for AI agents and automated systems in line with enterprise standards

•Support operationalising of Generative AI solutions, including LLM applications, RAG and emerging AI use cases

•Contribute to reusable templates, tooling and MLOps practices that make it easier to deploy new models consistently

•Contribute to establishing best practice, configure and set up state of the art tooling to meet production standards

•Support performance optimisation and efficient use of Databricks and cloud infrastructure