Senior Machine Learning Engineer

HCA Healthcare is an organization dedicated to investing in its team members, and they are seeking a Senior Machine Learning Engineer to join their team. This role involves driving the implementation of AI Platform capabilities, contributing to AI development, and collaborating with product and platform teams to enhance AI delivery through engineering excellence.

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 practice - 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
• 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