Machine Learning Engineer II

7-Eleven is an iconic family of brands with over 86,000 locations, surpassing every retailer in the world. We revolutionize convenience, restaurants, and fuel through cutting-edge innovation — working hard to be the customer's first choice. 7-Eleven empowers our employees to "activate awesome" and make a meaningful impact in their stores and communities every day. If you're ready to grow, lead, and make a difference, come join our team and help shape the future of convenience.

We are seeking a talented Machine Learning Engineer to design, develop, and deploy scalable machine learning solutions that drive business value as part of our digital initiatives. As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and work closely with senior architects to implement scalable and efficient data solutions. Your expertise in big data technologies, cloud-based data platforms, and machine learning model development will contribute to the transformation of telemetry data and other large datasets into actionable insights.

Key Responsibilities:

• Design, develop, test, and deploy machine learning models and data-driven solutions that transform store equipment telemetry data into actionable insights.
• Work in enterprise environments to build and optimize scalable data pipelines using Python, PySpark, and Azure-based technologies.
• Process, analyze, and manipulate large structured and unstructured datasets to support analytics and machine learning initiatives.
• Collaborate with data engineers, data scientists, product owners, and business stakeholders to translate business requirements into technical solutions.
• Develop, evaluate, and tune machine learning models using appropriate algorithms and statistical techniques.
• Implement MLOps best practices for model deployment, monitoring, and lifecycle management.
• Create visualizations, dashboards, and presentations to communicate insights and recommendations to technical and non-technical audiences.
• Participate in code reviews, technical design discussions, and continuous improvement initiatives.

Required Qualifications:

• Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
• 5+ years of experience delivering big data and machine learning solutions in enterprise environments.
• Strong programming experience in Python and PySpark.
• Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS), Git, and Azure DevOps.
• Experience building, training, validating, and deploying machine learning models.
• Solid understanding of data structures, algorithms, software engineering principles, and distributed computing concepts.
• Experience working with large-scale datasets and cloud-native architectures.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications:

• Experience deploying and operationalizing machine learning models in Azure Databricks.
• Experience with MLOps frameworks and CI/CD pipelines for machine learning workloads.
• Experience with data visualization tools such as Power BI, Tableau, or equivalent platforms.
• Experience working with equipment telemetry data or on equipment maintenance projects.
• Knowledge of containerization technologies and cloud-native application development.

Machine Learning Expertise:

• Clustering and segmentation techniques.
• Generalized Linear Models (GLM), Linear Regression, and Logistic Regression.
• Decision Trees and Random Forests.
• Gradient boosting techniques including XGBoost.
• K-Nearest Neighbors (KNN).
• Support Vector Machines (SVM).
• Artificial Neural Networks (ANN) and deep learning concepts.
• Model evaluation, feature engineering, hyperparameter tuning, and performance optimization.

Success Factors:

• Ability to work effectively in a fast-paced, collaborative environment.
• Strong ownership mindset and commitment to delivering high-quality solutions.
• Ability to communicate complex technical concepts to diverse stakeholder groups.
• Passion for continuous learning and innovation in machine learning and cloud technologies.