Senior Decision Intelligence Engineer - Remote-Eligible

Humana Inc; Baton Rouge (LA); Hybrid; USD 107,000 - 147,000; Full time

Benefits offered by this job

Bonus incentive plan

Remote/Hybrid work

Job summary

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

You will own end-to-end development, deployment, and monitoring, collaborating with ML, data, and decision engine teams to ensure scalable, auditable, and compliant outcomes. The role emphasizes MLOps, feature engineering, and optimization-aware decisioning across a large-scale platform with a health-focused context.

Qualifications

• Bachelor's degree in computer science or a related field.
• 5+ years building and operating large-scale production systems, data-intensive platforms serving millions of users.
• 2+ years building/operating production systems for data-intensive platforms with millions of users.
• 2+ years implementing reinforcement learning or simulation-driven decision systems in production.
• Deep familiarity with MDPs, Bellman equations, and reward shaping in real-world decision systems.
• Proficiency in Python 3.x; experience with PyTorch or TensorFlow for policy networks.

Responsibilities

• Build, deploy, and operate ML and decisioning pipelines for production systems.
• Develop and maintain production ML pipelines with strong MLOps practices.
• Collaborate with ML engineers, data/platform engineers, product owners, and decision engine teams.
• Monitor, debug, and optimize models for stability, scalability, and auditable decisions.

Skills

Python

Reinforcement Learning

MLOps

Production Systems

Monitoring

Experiment Tracking

Distributed Training

Education

Bachelor's degree in CS or related field

Tools

PyTorch

TensorFlow

Ray RLlib

Databricks

PySpark

Delta Lake

MLflow

Job description

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

You will own end-to-end development, deployment, and monitoring, collaborating with ML, data, and decision engine teams to ensure scalable, auditable, and compliant outcomes. The role emphasizes MLOps, feature engineering, and optimization-aware decisioning across a large-scale platform with a health-focused context.