Senior Decision Intelligence Engineer (Remote/Hybrid)

Humana Inc

Sacramento (CA)

Hybrid

USD 107,000 - 147,000

Full time

5 days ago
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Benefits offered by this job

Bonus incentive plan
Remote/Hybrid work option

Job summary

Humana Inc. is seeking a Senior Machine Learning Engineer for the Decision Intelligence platform.

This hands-on role develops, deploys, and operates ML and decisioning pipelines at scale, focusing on production pipelines, MLOps, feature engineering, and monitoring. You will partner with ML engineers, data engineers, platform engineers, product owners and decision engine teams to deliver reliable, auditable production systems and optimize decisions for members within clinical and program

Qualifications

  • Bachelor's degree in CS or related field required.
  • 5+ years building and operating large-scale production systems with data-intensive platforms.
  • 2+ years with production reinforcement learning or simulation-based decision systems.
  • Proficiency in Python 3.x with PyTorch or TensorFlow.
  • Experience with distributed frameworks like Ray RLlib.

Responsibilities

  • Build, deploy, and operate ML and decisioning pipelines for production systems.
  • Develop and optimize production ML workflows with MLOps practices.
  • Collaborate with ML engineers, data engineers, and platform teams to ensure reliable systems.
  • Ensure auditable, scalable, and compliant decisioning across member actions.

Skills

Python
PyTorch
TensorFlow
Ray RLlib
Databricks
PySpark
Delta Lake
MLflow

Education

Bachelor's degree in Computer Science

Tools

Databricks
PySpark
Delta Lake
MLflow

Job description

Humana Inc. is seeking a Senior Machine Learning Engineer for the Decision Intelligence platform.

This hands-on role develops, deploys, and operates ML and decisioning pipelines at scale, focusing on production pipelines, MLOps, feature engineering, and monitoring. You will partner with ML engineers, data engineers, platform engineers, product owners and decision engine teams to deliver reliable, auditable production systems and optimize decisions for members within clinical and program

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