Machine Learning Engineer II

Machine Learning Engineer II role focused on turning store telemetry and large datasets into scalable, actionable machine learning insights.

Responsibilities

• Design, develop, test, and deploy machine learning models and data-driven solutions using store equipment telemetry data to produce actionable insights.
• Build and optimize scalable data pipelines in enterprise environments 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 convert business requirements into technical solutions.
• Develop, evaluate, and tune machine learning models using appropriate algorithms and statistical techniques.
• Apply MLOps best practices for model deployment, monitoring, and lifecycle management.
• Create visualizations, dashboards, and presentations to communicate insights and recommendations to both technical and non-technical audiences.
• Participate in code reviews, technical design discussions, and continuous improvement efforts.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.
• 5+ years delivering big data and machine learning solutions in enterprise environments.
• Strong programming background 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.

Technology Stack

• Python, PySpark, Azure
• Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS)
• Git, Azure DevOps
• Power BI, Tableau

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 with a commitment to high-quality delivery.
• Ability to communicate complex technical concepts to diverse stakeholder groups.
• Passion for continuous learning and innovation in machine learning and cloud technologies.

Location: Irving, TX (onsite)

Experience: 5 years minimum