Remote ML Engineer - Healthcare Payer & Databricks

UST; Chicago (IL); Remote; USD 82,000 - 123,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Paid vacation

Paid sick leave

HSA/FSA

Job summary

UST is seeking a Machine Learning Engineer to design, build, and deploy ML models across healthcare payer data including claims, clinical, provider, and Medicare Advantage data. The role emphasizes feature engineering on Databricks, model lifecycle management, and responsible deployment to production.

You will partner with data engineers, compliance, and product teams to translate business problems into ML solutions while ensuring HIPAA-aligned security and governance.

Qualifications

• 2-4 years of hands-on ML engineering or applied data science lifecycle experience.
• Proficiency in Python and ML libraries/frameworks (scikit-learn, PyTorch, TensorFlow, MLflow).
• Experience building, training, and deploying models on Databricks, including feature engineering and model serving.

Responsibilities

• Design, build, and validate ML models for healthcare payer use cases.
• Develop and maintain feature engineering pipelines on Databricks.
• Train, tune, and evaluate models with standard ML frameworks and manage lifecycle.

Skills

Python

scikit-learn

PyTorch

TensorFlow

Databricks

AWS

MLflow

CI/CD

Model deployment

Data security

Communication

Tools

Databricks

MLflow

Job description

UST is seeking a Machine Learning Engineer to design, build, and deploy ML models across healthcare payer data including claims, clinical, provider, and Medicare Advantage data. The role emphasizes feature engineering on Databricks, model lifecycle management, and responsible deployment to production.

You will partner with data engineers, compliance, and product teams to translate business problems into ML solutions while ensuring HIPAA-aligned security and governance.