Senior MLOps Engineer - Production ML & Databricks

Dow; Town of Texas (WI); Vor Ort; USD 140.000 - 180.000; Vollzeit

Benefits dieser Stelle

Competitive compensation

Bonus opportunities

Excellent health & retirement benefits

Zusammenfassung

Dow is seeking a Machine Learning Engineer within its Enterprise Data & AI organization, based in Houston, TX; Midland, MI; or Champaign, IL. You will architect and deploy production-grade ML solutions, lead MLOps practices, and collaborate with data scientists, engineers, and business teams on end-to-end projects.

This role emphasizes modern software engineering, governance, and scalable ML workflows across Databricks-first environments, with opportunities to impact multiple business areas.

Qualifikationen

• Bachelor’s degree or equivalent experience required; U.S. work authorization stated.
• Minimum three years in ML, data science, software/data eng, or related field.
• Ability to work legally in the United States; no visa sponsorship provided.

Aufgaben

• Design and own the enterprise MLOps framework architecture and roadmap.
• Lead adoption of modern software engineering and MLOps practices across teams.
• Hands-on ML engineering on priority use cases; deploy production-grade models.
• Collaborate with data scientists, engineers, and stakeholders to deliver end-to-end solutions.

Kenntnisse

MLOps Architecture

Technical Leadership

Production ML Engineering

Databricks & Azure

Software Engineering

Security & Governance

Ausbildung

Bachelor’s degree or equivalent (military experience acceptable)

Tools

Databricks

Azure DevOps

Python

PySpark

SQL

MLflow

Delta Lake

Unity Catalog

Jobbeschreibung

Dow is seeking a Machine Learning Engineer within its Enterprise Data & AI organization, based in Houston, TX; Midland, MI; or Champaign, IL. You will architect and deploy production-grade ML solutions, lead MLOps practices, and collaborate with data scientists, engineers, and business teams on end-to-end projects.

This role emphasizes modern software engineering, governance, and scalable ML workflows across Databricks-first environments, with opportunities to impact multiple business areas.