Machine Learning Engineer - Production ML on Azure Databricks

Dow; Illinois; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive pay

Bonus opportunity

Stock purchase program

Wellbeing program

PTO

On-site gym

Job summary

Dow is seeking a Machine Learning Engineer for its Enterprise Data & Analytics group in Houston, TX; Midland, MI; or Champaign, IL. You will design, deploy, and monitor ML systems, collaborating with data engineers, scientists and software engineers to deliver production-grade AI/ML solutions on the Azure Databricks platform.

You’ll implement end-to-end ML lifecycles, drive standards for MLOps, and communicate results with stakeholders through Databricks notebooks and dashboards.

Qualifications

• Bachelor's degree or 8 years relevant experience required.
• 3+ years in machine learning, data science, or related field.
• Authorized to work in the United States without visa sponsorship.

Responsibilities

• Design and implement AI/ML pipelines for online, batch, or real-time inference.
• Deploy and monitor models in production using Databricks tools.
• Collaborate with data engineers, DevOps, data scientists and domain experts.
• Work with various ML frameworks (TensorFlow, PyTorch, scikit-learn) and Spark-based tools.
• Perform data analysis, feature engineering, model selection, and evaluation.
• Document results and communicate insights to stakeholders using notebooks and dashboards.

Skills

Solutions Delivery

Cloud Computing

Integration Services

Security Awareness

Strategic Planning

Education

Bachelor's degree

Tools

Python

Databricks

Azure Kubernetes Service

Apache Spark

Databricks MLflow

Delta Lake

Azure DevOps

SQL Analytics

Job description

Dow is seeking a Machine Learning Engineer for its Enterprise Data & Analytics group in Houston, TX; Midland, MI; or Champaign, IL. You will design, deploy, and monitor ML systems, collaborating with data engineers, scientists and software engineers to deliver production-grade AI/ML solutions on the Azure Databricks platform.

You’ll implement end-to-end ML lifecycles, drive standards for MLOps, and communicate results with stakeholders through Databricks notebooks and dashboards.