Lead Machine Learning Engineer - Decision Support Platform

Humana

United States

United States

Ähnliche Jobs finden

Über

Join Us in Prioritizing Health! We are excited to invite applications for the Lead Machine Learning Engineer position, focusing on the development and management of advanced machine learning systems that support real-time, personalized decision-making across diverse channels. Our cutting-edge platforms utilize predictive modeling, optimization strategies, and contextual data to deliver relevant actions swiftly and reliably. This position emphasizes production machine learning engineering. You will take the lead in constructing machine learning pipelines, online inference services, and decision-time scoring frameworks, leveraging state-of-the-art solutions to enhance development speed, model quality, and operational efficiency. Key Responsibilities Machine Learning System Design & Architecture
Oversee comprehensive design and management of machine learning systems, including: Feature engineering and reuse strategies. Development of offline training and online inference pipelines. Implementation of model versioning and rollback processes. Ensure systems meet high standards for latency, scalability, reliability, and accuracy. Maintain a clear separation between model development and deployment.
Decision-Centric Modeling
Build and operationalize various models, including: Propensity and likelihood predictions. Uplift or incremental impact models. Engagement and responsiveness scoring systems. Design models to be composable, interpretable, and robust for automated workflows. Collaborate with analytics and product teams to translate business goals into measurable modeling outcomes.
Efficiency Through AI
Integrate AI methodologies to boost ML engineering productivity, such as: Automated code generation and refactoring for pipelines. Feature exploration and validation approaches. Intelligent experiment tracking and comparative analysis. Robust debugging and root-cause analysis techniques. Evaluate and adopt modern tools to enhance experimentation and streamline operations.
MLOps & Model Operations
Establish and uphold strong MLOps practices, including: Continuous model training and deployment pipelines. Monitoring model performance for latency and drift. Implementing secure rollout strategies, including canary, shadow, or phased releases. Developing fallback mechanisms for model failures. Ensuring model outputs are traceable, reproducible, and auditable.
Collaboration & Leadership
Serve as the technical lead in ML engineering, establishing best practices and standards. Collaborate with software engineers, data engineers, and platform teams for seamless ML integration. Mentor fellow machine learning engineers, fostering team growth and expertise. Influence architectural decisions to enhance testability and resilience.
Role Significance This role is vital in building trust and enhancing user experience through automated decision-making. Your expertise will guarantee our machine learning systems are accurate, reliable, interpretable, and easy to maintain. Make a Difference! Required Qualifications 8+ years of experience in machine learning engineering or data-driven platform development. 3+ years in a senior ML engineering or lead technical role. Extensive knowledge in: Feature engineering and data pipeline creation. Model training and performance evaluation. Implementing real-time inference systems. Strong programming skills in Python, Java, or related languages. Preferred Qualifications Experience with personalization or recommendation systems. Familiarity with distributed or event-driven architectures. Background in deploying models in regulated environments. Understanding of model explainability and fairness principles. Success Criteria Models consistently deliver reliable performance in decision-making. ML systems scale efficiently with manageable operational costs. Experimentation is efficient, consistent, and quantifiable. Engineering teams trust and comprehend model outputs. AI tools yield measurable improvements in development efficiency and model accuracy. Additional Information This position may require occasional in-office attendance for training or meetings at the following locations: Washington, D.C. metropolitan area Louisville, KY metropolitan area Denver, CO metropolitan area Dallas, TX metropolitan area Ft. Lauderdale, FL metropolitan area Remote NY Compensation The estimated salary range is $129,300 - $177,800 per year, depending on experience and qualifications. This position is eligible for a performance-based bonus incentive plan. Benefits Humana provides a comprehensive benefits package aimed at supporting whole-person well-being, including medical, dental, and vision plans, a 401(k) retirement savings plan, generous paid time off, short-term and long-term disability coverage, and life insurance, among other opportunities. Application Deadline: 04-02-2026 About Humana Humana Inc. is committed to prioritizing health for our employees, customers, and communities, making healthcare accessible and meaningful for all. Equal Opportunity Employer Humana maintains a policy of non-discrimination in all employment actions and takes proactive measures to ensure equal opportunities for all applicants.

United States

Sprachkenntnisse

English

Hinweis für Nutzer

Dieses Stellenangebot wurde von einem unserer Partner veröffentlicht. Sie können das Originalangebot einsehen hier.

Ähnliche Jobs finden