Lead RL Engineer - Healthcare Decision Intelligence, Remote

Humana Inc; Augusta (ME); Hybrid; USD 129,000 - 178,000; Full time

Job summary

Humana Inc. is seeking a Decision Intelligence Engineer to design, train, and continuously improve the reinforcement learning policy powering the Next Best Action platform for millions of members.

The role is hands-on and research-oriented, requiring collaboration with data engineers and platform teams, feature engineering from large healthcare datasets, and ensuring compliance with clinical rules. Remote/hybrid with travel as needed.

Qualifications

• Bachelor's degree in computer science or related field required.
• 8+ years of software engineering experience building and operating large-scale production systems, with emphasis on data-intensive platforms.
• 3+ years of hands-on experience implementing reinforcement learning or deep learning systems in production.

Responsibilities

• Design, implement, and evaluate RL algorithms suited to long-horizon, sparse-reward healthcare decisioning.
• Define and maintain the member state representation and action space, evolving both as new programs and data sources are onboarded.
• Apply the Bellman equation, reward shaping, and constraint mapping to encode clinical eligibility and program objectives.
• Manage exploration-exploitation tradeoffs in production healthcare environments.
• Build simulation and backtesting environments to evaluate policy quality before production.
• Instrument training runs with MLflow tracking hyperparameters and performance metrics.

Skills

Reinforcement learning in production

Python proficiency

Distributed RL training

Production ML systems

Education

Bachelor's degree in computer science or related field

Tools

PyTorch

TensorFlow

Ray RLlib

MLflow

Databricks

PySpark

Delta Lake

Redis

Job description

Humana Inc. is seeking a Decision Intelligence Engineer to design, train, and continuously improve the reinforcement learning policy powering the Next Best Action platform for millions of members.

The role is hands-on and research-oriented, requiring collaboration with data engineers and platform teams, feature engineering from large healthcare datasets, and ensuring compliance with clinical rules. Remote/hybrid with travel as needed.