Note: The job is a remote job and is open to candidates in USA. HCA Healthcare is seeking a Staff Machine Learning Engineer to lead the technical implementation and adoption of AI Platform capabilities within an embedded product team. The role involves hands-on development of AI/MLOps systems, establishing engineering standards and platform patterns, implementing ML model CI/CD pipelines, and mentoring other Machine Learning Engineers.
Responsibilities
- Partner with platform and product managers to identify and prioritize foundational platform capabilities
- Informs the definition and implementation of technical standards and patterns across the platforms and product teams
- Collaborates on technical and architectural direction for critical platform components
- Participates in technical discussions and decision-making processes for key platform features
- Mentors embedded MLEs in engineering best practices and platform tooling and adoption
- Helps 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
Skills
- • 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
- • 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
- • Remote (U.S. Only) - M-F, 8am – 5pm - Central Time
- • This job requires travel to Nashville, TN to attend final interview, 3-day New Hire Orientation, quarterly team meetings, and other travel on an as-needed basis
- • Not offered, now or in the future
- • Master's degree - Preferred
- • Experience working in as an embedded engineer in a cross function 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
Benefits
- Remote (U.S. Only)
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