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 worlds
• Make a Difference. Take a paid day off each year to volunteer for a cause you’re passionate about
• Fuel Your Day. Enjoy free 7-Eleven coffee and snacks in the office—because great ideas start with great coffee
• Family 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 most
• Stay Social & Connected. Join our Social Club and Open Committee for regular events, celebrations, and fun activities
• Grow 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 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 our 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 our 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
  

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 environments
• Experience with Azure Databricks and the Databricks ecosystem, including MLflow, Delta Lake, Unity Catalog and Workflows
• Experience deploying, operating and monitoring machine learning models in production, including drift detection and performance/data quality alerting
• Experience with CI/CD and software engineering practices for data or ML applications, ideally using Azure DevOps
• Established skill set in setting up unit and integration testing frameworks in the context of AI/Machine learning projects
• Experience with data processing performance optimisation and tuning
• Understanding 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 frameworks
• AI agent management, tooling, MCP orchestration
• Azure cloud services supporting AI and machine learning workloads
• Databricks 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 [email protected].

** 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.