Lead Decision Intelligence Engineer

🕒 6 dias atrás

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $129.300 - $177.800 / ano

⏰ Tempo Integral

🟠 Sênior

👷🏻‍♀️ Engenheiro

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Humana

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1961

🏥 Saúde

🛡️ Seguros

⚕️ Seguro de Saúde

Healthcare • Insurance • Healthcare Insurance

A Humana é uma empresa de saúde dedicada a gerar um impacto positivo na saúde de indivíduos, comunidades e do sistema de saúde como um todo. Com foco em colocar a saúde em primeiro lugar, a Humana atende a uma ampla e diversa gama de populações, incluindo idosos e militares, oferecendo planos Medicare Advantage (HMO, PPO e PFFS). A Humana está comprometida em promover uma cultura de pertencimento e respeito mútuo, oferecendo benefícios competitivos e flexíveis para garantir a segurança financeira de seus funcionários e de suas famílias. A empresa se orgulha de criar um ambiente de trabalho inclusivo, no qual todos têm a oportunidade de ter sucesso.

Descrição

• 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

🎯 Requisitos

• 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

🏖️ Benefícios

• 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