Senior ML Engineer

HCA Healthcare is seeking a Senior ML Engineer to drive the implementation of AI Platform capabilities within an embedded product team. The role involves hands-on development, contributing to AI/MLOps challenges, and ensuring effective adoption of platform capabilities.

Responsibilities:

• Actively contribute to AI/MLOps development within assigned product team
• Implement platform capabilities and patterns effectively
• Write high-quality, maintainable code following team standards
• Develop and maintain ML systems using platform capabilities
• Implement robust CI/CD pipelines for ML models
• Ensure proper testing and validation of ML systems
• Balance team-specific needs with platform standardization
• Champion platform adoption within a team
• Follow and help refine platform patterns and best practices
• Identify opportunities for leveraging platform capabilities
• Provide feedback on platform features and usability
• Help validate platform patterns through direct implementation
• Share knowledge and experiences with other MLEs
• Contribute to platform documentation and examples
• Participate in code reviews with focus on platform patterns
• Implement and maintain ML pipelines using platform tools
• Document technical decisions and implementations
• Follow established best practices and standards
• Contribute to technical discussions and design reviews
• Work closely with product team to understand AI development needs
• Provide implementation feedback to platform team
• Participate in technical discussions and knowledge sharing
• Help identify opportunities for platform improvement

Requirements:

• Bachelor's degree - Required
• 5+ 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
• Strong Python development expertise with focus on ML systems and AI/MLOps - Required
• Familiarity of ML workflows and operational requirements - Required
• Hands-on experience implementing model CI/CD pipelines - Required
• Experience with modern Python development practices including type checking, testing frameworks, and package management - Required
• History of successful collaboration with product teams - Required
• Familiarity with ML Development Lifecycle management and MLOps best practices - Required
• Familiarity of ML Monitoring and observability - Required
• Master's degree - Preferred
• Experience working in as an embedded engineer in a cross-function product team - Preferred
• Experience with LLMs and Infrastructure - Preferred
• Familiarity integrating with feature stores, feature caches and model serving platforms - Preferred
• Understanding of ML/AI platform tooling and patterns - Preferred
• Familiarity with Distributed model training - Preferred
• Hands-on experience with Kubeflow, Argo, MLFlow or other ML/AI Training orchestrators - Preferred
• Familiarity of ML/AI metadata tools and model registries – Preferred
• Hands-on experience with Terraform or other IaC tools - Preferred
• Hands on experience building ML/AI solutions on GCP and Vertex AI - Preferred
• Familiarity with ML model lifecycle and common ML libraries (PyTorch, scikit-learn, XGBoost, AutoGluon, CatBoost, TensorFlow, Keras) - Preferred
• Familiarity with major LLM Models (Gemini, Cluade, ChatGPT, DeepSeek, LLaMA) - Preferred
• Experience with FastAPI and async Python development - Preferred
• Familiarity with modern Python tooling (uv, mypy, ruff, bandit) - Preferred
• Experience with prompt management and versioning systems - Preferred
• Understanding of RAG architectures and token optimization - Preferred
• Experience writing and optimizing ML/AI tooling and components in C++ or Rust - Preferred
• Experience integrating with feature stores, feature caches and model serving platforms – Preferred