Production ML Engineer | Azure Databricks & MLOps

dow; Houston (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equitable base pay & bonus opportunity

Comprehensive medical & life insurance

Employee stock purchase program

Paid time off and family leave

Retirement & financial planning

Job summary

Dow is seeking a Machine Learning Engineer to design, develop, and deploy production-ready ML systems on site in Houston, TX (also in Midland, MI or Champaign, IL). You will build end-to-end ML workflows, deploy models, and maintain operations with robust MLOps using Azure Databricks, MLflow, and related tools.

You will collaborate with data engineering, DevOps, and software teams to deliver reliable AI capabilities while adhering to IT security policies and governance.

Qualifications

• Bachelor's degree or 8 years of relevant experience, or military E6 or higher.
• At least 3 years in ML, data science, or related field.
• Ability to work legally in the United States; no visa sponsorship provided.

Responsibilities

• Design and implement end-to-end ML pipelines for online, batch, and real-time inference.
• Deploy and monitor ML models in production using Databricks tools.
• Collaborate with data engineers, DevOps, data scientists, and developers to deliver scalable AI/ML solutions.
• Work with application teams to enable integration and secure designs.
• Document results and insights using Databricks notebooks and dashboards.

Skills

End-to-end ML workflows

Model deployment

MLOps practices

Collaboration across teams

Education

Bachelor's degree

Tools

Azure Databricks

Databricks MLflow

Delta Lake

SQL Analytics

Model Registry

Databricks Jobs/Workspace

TensorFlow

PyTorch

scikit-learn

Keras

Spark MLlib

Ray

Azure DevOps

Job description

Dow is seeking a Machine Learning Engineer to design, develop, and deploy production-ready ML systems on site in Houston, TX (also in Midland, MI or Champaign, IL). You will build end-to-end ML workflows, deploy models, and maintain operations with robust MLOps using Azure Databricks, MLflow, and related tools.

You will collaborate with data engineering, DevOps, and software teams to deliver reliable AI capabilities while adhering to IT security policies and governance.