Staff ML Engineer

The Staff Machine Learning Engineer leads technical implementation and adoption of AI Platform capabilities within an embedded product team while serving as a technical leader and mentor for other Machine Learning Engineers. Actively contributes to AI Platform and operations development through hands‑on coding while establishing best practices, standardizing implementation patterns, and driving platform adoption. Advocates for platform solutions, ensuring consistent application of engineering standards, and accelerating AI delivery through effective platform usage and technical mentorship. Major 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 Education & Experience: Bachelor's degree - Required Master's degree - Preferred 7+ years of experience in software engineering with a focus on ML and AI System Engineering - Required Experience working in as an embedded engineer in a cross function product team - Preferred Knowledge, Skills, Abilities, Behaviors: 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 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 Work Location/Schedule: Remote (U.S. Only) - M-F, 8am - 5pm - Central Time Travel Required: 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 Virtual Interviews: All HCA Healthcare virtual interviews are conducted without the use of virtual backgrounds, background blurring, or any other visual distortion tools. AI Usage Policy: The use of AI tools or prompts during any part of the interview is strictly prohibited. If it appears that you are reading from a script or using AI‑generated responses, you will be eliminated from further consideration. We value authenticity and want to hear your own thoughts and experiences. #J-18808-Ljbffr HCA Healthcare