Lead Machine Learning Engineer

HCA Healthcare is seeking a Lead Machine Learning Engineer to spearhead the technical implementation and adoption of AI Platform capabilities. This role involves mentoring other Machine Learning Engineers and driving platform adoption through hands-on coding and establishing best practices.

Responsibilities:

• Partner with platform and product managers to identify and prioritize foundational platform capabilities
• Inform the definition and implementation of technical standards and patterns across the platforms and product teams
• Collaborate on technical and architectural direction for critical platform components
• Participate in technical discussions and decision-making processes for key platform features
• Mentor embedded MLEs in engineering best practices and platform tooling and adoption
• Help evaluate and make recommendations on technical approaches and new technologies
• Actively contribute to AI/MLOps development within assigned product team
• Drive adoption of platform capabilities through example and technical guidance
• Implement and validate platform patterns within pod
• Help identify and solve common challenges across pods
• Balance pod-specific needs with platform standardization
• Champion platform adoption within pod and across teams
• Provide technical guidance on platform usage and implementation
• Identify opportunities for leveraging platform capabilities
• Contribute to platform feature development and improvement
• Help validate and refine platform patterns through direct implementation
• Share knowledge and best practices across the MLE team
• Implement robust CI/CD pipelines for ML models
• Develop and maintain ML systems using platform capabilities
• Ensure proper testing and validation of ML systems
• Document technical decisions and implementation patterns
• Partner with platform team to improve developer experience
• Conduct thorough code reviews with focus on platform patterns
• Contribute to technical design discussions and architecture reviews

Requirements:

• Bachelor's degree – Required
• 7+ years of experience in software engineering with a focus on ML and AI System Engineering – Required
• Strong technical background in ML engineering with demonstrated coding expertise –Required
• Track record of driving adoption of technical platforms and developer tools –Required
• Deep Python development expertise with focus on ML systems and AI/MLOps –Required
• Proven ability to establish and maintain technical standards –Required
• Strong understanding of ML workflows and operational requirements –Required
• Hands-on experience implementing and scaling model CI/CD pipelines –Required
• Experience with modern Python development practices including type checking, testing frameworks, and package management –Required
• Experience with modern Python development practices including type checking and testing –Required
• History of successful collaboration with product teams –Required
• Understanding of ML Development Lifecycle management and MLOps best practices –Required
• Understanding of ML Monitoring and observability –Required
• Master's degree – Preferred
• Experience working as an embedded engineer in a cross-functional product team – Preferred
• Experience with LLMs and Infrastructure –Preferred
• Experience integrating with feature stores, feature caches, and model serving platforms –Preferred
• Deep understanding of ML/AI platform tooling and patterns –Preferred
• Experience with Distributed model training –Preferred
• Hands-on experience with Kubeflow, Argo, MLFlow or other ML/AI Training orchestrators –Preferred
• Hands-on experience and knowledge of ML/AI metadata tools and model registries –Preferred
• Deep hands-on experience with Terraform or other IaC tools –Preferred
• Hands-on experience building ML/AI solutions on GCP and Vertex AI –Preferred