Staff Data Engineer

Job summary

Job Location: Dallas, TX Summary The Staff Data Engineer, MLOps leads the design, build, and optimization of Hershey’s machine learning operations platform—enabling data science and AI teams to develop, deploy, monitor, and govern ML models at enterprise scale.

Responsibilities

• This is a foundational role—you will define and build Hershey’s MLOps capability from the ground up, shaping the platform, establishing engineering standards, and growing the team as the function matures.
• ML Platform Engineering & Infrastructure
• Design and maintain the end-to-end MLOps platform on Azure and Databricks: model training infrastructure, feature stores, experiment tracking, model registries, and serving endpoints.
• Build and optimize CI/CD pipelines for automated model training, validation, packaging, and deployment across environments.
• Model Deployment, Monitoring & Lifecycle Management
• Implement model serving patterns (batch, real-time, edge) with blue-green and canary deployment strategies for safe rollouts.
• Build monitoring frameworks for data drift, concept drift, and prediction quality; automate alerting and retraining triggers.
• Governance, Reproducibility & Responsible AI
• Enforce ML governance: model versioning, experiment lineage, artifact management, approval workflows, and audit trails.
• Embed responsible AI practices including explainability tooling, bias detection, and documentation standards.
• Infrastructure as Code & Cost Optimization
• Author IaC (Terraform/Bicep) for Azure ML workspaces, Databricks clusters, networking, and compute; optimize costs through autoscaling, spot instances, and GPU scheduling.

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