Lead Decision Intelligence Engineer

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $129.3k - $177.8k / year

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

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Humana

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1961

🏥 Healthcare

🛡️ Insurance

⚕️ Healthcare Insurance

Healthcare • Insurance • Healthcare Insurance

Humana is a healthcare company dedicated to making a positive impact on the health of individuals, communities, and the healthcare system as a whole. With a focus on putting health first, Humana serves a diverse range of populations, including seniors and the military, providing Medicare Advantage HMO, PPO, and PFFS plans. Humana is committed to fostering a culture of belonging and mutual respect, offering competitive and flexible benefits to ensure the financial security of its employees and their families. The company prides itself on creating an inclusive workplace where everyone has the opportunity to succeed.

📋 Description

• Design, implement, and evaluate reinforcement learning algorithms for long-horizon, sparse-reward healthcare decisioning • Define and maintain member state representations and action spaces • Apply Bellman equation, reward shaping, and constraint mapping to encode clinical eligibility and program objectives • Manage exploration-exploitation tradeoffs in a production healthcare environment • Build simulation and backtesting environments using historical member journey data • Diagnose and remediate RL failure modes, including policy collapse, credit assignment errors, and distributional shift • Define reward thresholds and automated evaluation gates in nightly Databricks workflows • Block underperforming policy promotion to MLflow production • Instrument training runs with MLflow tracking • Own nightly Databricks training workflows, feature engineering, distributed RL training, and batch scoring of 8 million eligible members • Write production-quality PySpark feature engineering jobs and maintain data lineage through Databricks Unity Catalog • Manage model artifacts, versioning, lifecycle, and rollback capability in the MLflow Model Registry • Apply multi-agent reinforcement learning where household or population coordination is required • Implement constraints for member caps, cooldown periods, and clinical eligibility • Collaborate with Rules Engine, Data Engineering, Decision Engine, platform architecture, clinical, and compliance stakeholders • Integrate model outputs with real-time decisioning and Redis-cached recommendations • Define feedback loop contracts from disposition outcomes through Kafka and Databricks Delta Live Tables into retraining • Document model behavior, limitations, and failure modes • Support explainability requirements for member-facing decisions • Use AI-assisted engineering tools for scaffolding, testing, and documentation while keeping core model logic human-authored and peer-reviewed

🎯 Requirements

• Bachelor's degree in computer science or related field • 8+ years of software engineering experience building and operating large-scale production systems • Emphasis on data-intensive platforms, recommendation systems, or optimization engines serving millions of users • 3+ years of hands-on experience implementing reinforcement learning or deep learning systems in production • Experience with policy gradient methods including PPO and A3C, value-based approaches including DQN and Q-learning, or offline RL algorithms including CQL and Decision Transformer • Deep familiarity with the Bellman equation, reward shaping, exploration-exploitation tradeoff, and constraint mapping • Ability to diagnose policy collapse, credit assignment issues, and distributional shift • Proficiency in Python 3.x • Experience with PyTorch or TensorFlow • Experience with Ray RLlib • Experience with Databricks, PySpark, and Delta Lake • Experience with MLflow • Track record of shipping reliable ML systems under production load • Role is not eligible for work visa sponsorship • Minimum home internet speed of 25 Mbps download and 10 Mbps upload • Dedicated work space without ongoing interruptions to protect PHI/HIPAA information

🏖️ Benefits

• Bonus incentive plan based on company and/or individual performance • Medical, dental, and vision benefits • 401(k) retirement savings plan • Paid time off • Company and personal holidays • Paid parental and caregiver leave • Short-term and long-term disability • Life insurance • Flexible work hours may be possible depending on business needs • Remote work arrangement • Occasional travel to Humana offices for training or meetings • Dedicated home workspace requirement to protect member PHI/HIPAA information • Home internet service requirements and potential upgrade support if necessary