Senior Decision Intelligence Engineer - Remote ML & Optimization

Humana Inc; Indianapolis (IN); À distance; USD 107 000 - 147 000; Plein temps

Résumé du poste

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

You will build, deploy, and operate scalable systems with MLOps, feature engineering, and monitoring to ensure optimal member actions within constraints. You will collaborate across ML, data, and platform teams to deliver auditable, reliable production solutions, focusing on reinforcement learning and optimization in

Qualifications

• Bachelors in computer science or relevant field required.
• 5+ years of software engineering or quantitative research building large-scale production systems.
• 2+ years implementing reinforcement learning or simulation-based decision systems in production.
• Experience with Python 3.x and PyTorch or TensorFlow for policy networks.

Responsabilités

• Build, deploy, and operate ML and decisioning pipelines for the platform.
• Focus on production pipeline development, MLOps, and monitoring.
• Collaborate with ML engineers, data/ platform engineers, and product teams.
• Ensure auditable, scalable production systems with reliable performance.

Connaissances

Software engineering

Quantitative research

MLOps

Python

PyTorch

TensorFlow

Ray RLlib

Databricks

PySpark

Delta Lake

MLflow

Formation

Bachelors in computer science or relevant field

Outils

Databricks

PySpark

Delta Lake

MLflow

Ray RLlib

Description du poste

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

You will build, deploy, and operate scalable systems with MLOps, feature engineering, and monitoring to ensure optimal member actions within constraints. You will collaborate across ML, data, and platform teams to deliver auditable, reliable production solutions, focusing on reinforcement learning and optimization in