Senior Decision Intelligence Engineer Remote ML Production

Humana Inc; Pierre (SD); Hybrid; USD 107,000 - 147,000; Full time

Benefits offered by this job

Bonus incentive plan

Job summary

Humana Inc. is seeking a Senior Machine Learning Engineer, Decision Intelligence to build, deploy, and operate production ML and decisioning pipelines for the NBA Decision Intelligence Platform.

You will own end-to-end pipeline work, feature engineering, scoring workflows, monitoring, and optimization-aware decisioning. You will collaborate with ML/data/platform engineers, product owners, and decision engine teams to ensure scalable, auditable systems that respect eligibility, constraints, and

Qualifications

• 5+ years (post undergraduate) of software engineering or quantitative research experience building and operating large-scale production systems.

Responsibilities

• Build, deploy, and operate ML and decisioning pipelines for the NBA Decision Intelligence Platform.
• Focus on production pipeline development, MLOps, feature engineering, scoring workflows, monitoring, and optimization-aware decisioning.
• Collaborate with ML engineers, data engineers, platform engineers, product owners, and decision engine teams to deliver reliable, scalable production systems.
• Ensure the platform selects the right action for the right member while respecting clinical eligibility, suppression rules, channel constraints, program goals, and operational capacity.

Skills

Python

PyTorch

TensorFlow

Ray RLlib

Databricks

PySpark

Delta Lake

MLflow

Education

Bachelor's degree in computer science or relevant field

Tools

Databricks

PySpark

Delta Lake

MLflow

Job description

Humana Inc. is seeking a Senior Machine Learning Engineer, Decision Intelligence to build, deploy, and operate production ML and decisioning pipelines for the NBA Decision Intelligence Platform.

You will own end-to-end pipeline work, feature engineering, scoring workflows, monitoring, and optimization-aware decisioning. You will collaborate with ML/data/platform engineers, product owners, and decision engine teams to ensure scalable, auditable systems that respect eligibility, constraints, and