MLOps Engineer

Since 2024, 7-Eleven Australia has joined 7-Eleven international to be part of the biggest retail network across the world, represented in 20 countries with over 84,000 stores. We have big growth plans in Australia and a lot of opportunity for someone who wants to be part of ever growing retailer with a global footprint. Firstly, what we offer you! Vibrant Open Office in Richmond. Work in a dynamic, collaborative space that sparks creativity Work Your Way. Enjoy the perfect balance of remote flexibility and in-office collaboration—get the best of both worldsMake a Difference. Take a paid day off each year to volunteer for a cause you’re passionate aboutFuel Your Day. Enjoy free 7-Eleven coffee and snacks in the office—because great ideas start with great coffeeFamily comes first. Get up to 15 weeks of paid parental leave for the primary carer and up to 4 weeks for concurrent leave, so you can focus on what matters mostStay Social & Connected. Join our Social Club and Open Committee for regular events, celebrations, and fun activitiesGrow Without Limits. Access unlimited LinkedIn Learning courses and invest in your personal and professional development The role Reporting to the Head of Research, Analytics & Data Science, the MLOps Engineer will play a key role in helping our Data Science team deploy, operate and maintain machine learning and AI solutions in production. Working closely with our Data Scientists, Data Engineers and Technology teams, you will help bridge the gap between model development and production by implementing reliable deployment, monitoring and operational processes. The role will initially focus on the operationalising and ongoing support of our strategic machine learning engine hosted in Databricks, while also supporting a growing portfolio of predictive modelling, optimisation and AI use cases across the business. What You’ll Be Doing Partner with Data Science to take models from experimentation through validation, deployment and ongoing production managementImplement and maintain production workflows for data ingestion and processing, model execution, retraining, testing and deploymentBuild and maintain CI/CD pipelines and controlled release processes for machine learning and AI workloadsBuild and maintain robust data and feature pipelines required by machine learning and AI solutionsDiagnose production issues and work with Data Science and our Engineers to resolve model, data and platform problemsImplement appropriate access controls, security and governance within Databricks, including access and action permissions for AI agents and automated systems in line with our enterprise standardsSupport operationalising of Generative AI solutions, including LLM applications, RAG and emerging AI use casesContribute to reusable templates, tooling and MLOps practices that make it easier to deploy new models consistentlyContribute to establishing best practice, configure and set up state of the art tooling to meet production standardsSupport performance optimisation and efficient use of Databricks and cloud infrastructure What’s in your toolkit? You are a hands-on engineer with experience deploying and supporting data science and machine learning solutions in production environments. You enjoy working closely with Data Scientists and Engineers to turn analytical solutions in to reliable production workloads. Strong Python and SQL skills, with experience using PySpark in distributed data environmentsExperience with Azure Databricks and the Databricks ecosystem, including MLflow, Delta Lake, Unity Catalog and WorkflowsExperience deploying, operating and monitoring machine learning models in production, including drift detection and performance/data quality alertingExperience with CI/CD and software engineering practices for data or ML applications, ideally using Azure DevOpsEstablished skill set in setting up unit and integration testing frameworks in the context of AI/Machine learning projectsExperience with data processing performance optimisation and tuningUnderstanding of governance/guardrails for AI agents, permissions, audit/traceability, operational risk Experience in the following would be highly regarded: Deploying and operationalising agentic AI and LLM-based solutions in production, including RAG, vector search, evaluation versioning and agent orchestration frameworksAI agent management, tooling, MCP orchestrationAzure cloud services supporting AI and machine learning workloadsDatabricks certifications or equivalent practical experience At 7-Eleven our people are at the heart of everything we do. We are committed to creating a workplace that fosters inclusion and celebrates diversity. We strive to make every single 7-Eleven team member feel heard, valued, and respected no matter who they are or what diverse characteristics reflect their unique identity. We are proud to be a Diversity Council Australia Inclusive Employer 2025-2026 and Gold Accredited with the Australian Workplace Equity Index. At 7-Eleven, we are committed to ensuring that all prospective employees have the opportunity to perform at their best throughout our recruitment process. If you require any adjustments to support an inclusive and accessible experience, please contact us for a confidential discussion at peoplesupport@7eleven.com.au. Please note, this email is strictly for adjustment requests related to the recruitment process. Other inquiries sent to this mailbox will not be actioned. ** To find out more about our current opportunities follow us on LinkedIn or view our careers page.