[Remote] Lead Machine Learning Engineer – Next Best Action (NBA) Platform

Note: The job is a remote job and is open to candidates in USA. Humana Inc. is committed to putting health first and is seeking a Lead Machine Learning Engineer to architect, develop, and manage machine learning systems for real-time decision-making. This role will focus on production machine learning engineering and involve the creation of ML pipelines and decision-time scoring logic to enhance operational effectiveness.

Responsibilities

• Design and manage end-to-end machine learning systems, including:
• Feature engineering and reuse strategies
• Offline training pipelines
• Online inference and scoring services
• Model versioning, rollout, and rollback procedures
• Ensure systems meet stringent requirements for latency, scalability, reliability, and correctness in real-time contexts
• Define clear separation between model development, deployment, and downstream decision logic
• Build and operationalize models such as:
• Propensity or likelihood prediction
• Uplift or incremental impact models
• Engagement or responsiveness scoring
• Design models to be composable, explainable, and robust for automated decision workflows
• Collaborate with analytics and product teams to translate business objectives into measurable modeling outcomes
• Apply AI-assisted and agentic approaches to boost ML engineering productivity, including:
• Automated code generation and refactoring for pipelines and services
• Feature exploration and validation
• Intelligent experiment tracking and comparison
• Enhanced debugging and root-cause analysis
• Assess and adopt modern tools to accelerate experimentation, reduce manual overhead, and ensure reliable model operations
• Focus on implementing practical, production-ready AI tools
• Develop and sustain robust MLOps practices, including:
• Continuous training and deployment pipelines
• Online model monitoring for latency, drift, and stability
• Safe rollout strategies (e.g., canary, shadow, phased releases)
• Fallback mechanisms for model degradation or unavailability
• Guarantee model outputs are traceable, reproducible, and auditable
• Serve as the technical leader for ML engineering, establishing standards and best practices
• Partner with software engineers, data engineers, and platform teams to ensure seamless integration of ML systems into production
• Mentor machine learning engineers and contribute to the overall maturity of engineering teams
• Influence architectural decisions to ensure testability, observability, and resilience

Skills

• 8+ years of experience in machine learning engineering, applied ML, or data-driven platform development
• 3+ years in a technical lead or senior ML engineering capacity
• Deep expertise in: Feature engineering and data pipelines, Model training and evaluation, Real-time or near-real-time inference systems
• Strong software engineering skills in Python, Java, or similar languages
• Practical experience with AI-assisted development tools to streamline ML workflows
• Experience with personalization, recommendation, or decisioning platforms
• Familiarity with distributed systems and event-driven architectures
• Experience deploying models in regulated or high-reliability settings
• Knowledge of model explainability and fairness methodologies

Benefits

• Medical
• Dental and vision benefits
• 401(k) retirement savings plan
• Time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
• Short-term and long-term disability
• Life insurance

Company Overview

• Humana is a health insurance provider for individuals, families, and businesses. It was founded in 1964, and is headquartered in Louisville, Kentucky, USA, with a workforce of 10001+ employees. Its website is http://www.humana.com.

Company H1B Sponsorship

• Humana has a track record of offering H1B sponsorships, with 282 in 2025, 246 in 2024, 284 in 2023, 274 in 2022, 212 in 2021, 84 in 2020. Please note that this does not guarantee sponsorship for this specific role.