ML Platform Engineer — MLOps for Production-Grade Models

Diamondback E&P LLC; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Diamondback Energy seeks an ML Developer to establish MLOps practices and platform foundations for moving ML models from experimentation to production. You will work primarily with Databricks, defining model deployment, monitoring, and governance while coordinating with data science, data engineering, and IT teams to meet company objectives.

The role requires 3–5 years of hands-on ML experience, strong Python and SQL skills, and a track record of delivering production ML systems in a Databricks

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or related field.
• Hands-on experience with Databricks MLflow and AutoML.
• 3–5 years hands-on experience building, deploying, and operating ML/data-intensive systems in production.
• Strong Python proficiency with production-grade code.
• Strong SQL skills and knowledge of Spark or similar frameworks.
• Experience establishing/operating an MLOps workflow including deployment, monitoring, and lifecycle management.
• GIT, unit testing, CI/CD, and common design patterns.

Responsibilities

• Establish the department’s MLOps standards and golden path for taking a model to production.
• Partner with data science teams to productionize models using Databricks MLflow, AutoML, Unity Catalog, and Model Serving.
• Design and maintain automated CI/CD pipelines for model training, deployment, and promoted environments.
• Govern the model lifecycle with experiment tracking, registration, versioning, lineage, and access control.
• Establish model and data monitoring, validation checks, and operational observability; support incident response for production ML systems.
• Enforce data and feature quality, schema validation, and data versioning for trusted inputs.
• Author documentation, reference architectures, and playbooks; lead reviews and knowledge-sharing.
• Coordinate with stakeholders to define requirements and drive adoption of shared ML frameworks.
• Evaluate new tools and patterns, including agentic/LLM-assisted workflows, and recommend improvements.

Skills

Databricks MLflow

AutoML

Python

SQL

Spark

MLOps

Git

CI/CD

Unit testing

Communication

Education

Bachelor’s degree in CS/DS/Engineering

Tools

Databricks

Unity Catalog

MLflow

CI/CD tooling

Job description

Diamondback Energy seeks an ML Developer to establish MLOps practices and platform foundations for moving ML models from experimentation to production. You will work primarily with Databricks, defining model deployment, monitoring, and governance while coordinating with data science, data engineering, and IT teams to meet company objectives.

The role requires 3–5 years of hands-on ML experience, strong Python and SQL skills, and a track record of delivering production ML systems in a Databricks