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HCA Healthcare

Posted 21 Oct 2026

Consultant - AI Engineer

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Team
Digital Products
Posted
21 Oct 2026

About the role

General Position Information Job Title Identification: Consulting Machine Learning Engineer Reports directly to (Title): Director Matrix reports to (Title): As applicable based on functional alignment Direct Reports: Individual contributor role, no direct reports Position Summary: The Consulting Machine Learning Engineer develops and integrates machine learning models and pre-trained APIs with large-scale data ecosystems to support clinical, coding, revenue cycle, and other business use cases. This role applies deep expertise in cloud, data, and machine learning platforms to identify practical solutions that integrate structured and unstructured data and maximize the value of enterprise technology and data investments. The Consulting ML Engineer evaluates solution options during proof-of-concept activities, considering cost, long-term functionality, organizational standards, and technology roadmaps. This customer-facing role partners closely with data scientists, data engineers, clinical and business stakeholders to define questions, explore solutions, and present results. Key Responsibilities:
  • Design and develop NLP and machine learning applications on Google Cloud and enterprise data platforms using technologies such as Vertex AI, large language models (LLMs), and Document AI.
  • Apply NLP techniques for text representation, semantic extraction, data structures, modeling, and natural language understanding to solve complex business problems.
  • Transform data science prototypes into scalable solutions and extend machine learning libraries and frameworks for NLP use cases.
  • Select appropriate annotated datasets and supervised learning methods; identify and implement algorithms and tools suited to specific NLP tasks.
  • Integrate machine learning solutions with enterprise data platforms and source systems through APIs and other integration patterns.
  • Train and evaluate machine learning models, perform statistical analysis of results, and refine models to improve accuracy and business value.
  • Partner with clinical and business customers to define questions, assess solution options, and communicate findings and recommendations clearly.
  • Evaluate proof-of-concept solutions considering cost, long-term functionality, company policies, organizational vision, and technology roadmaps.
  • Provide technical leadership and guidance across machine learning, NLP, cloud, data, and API solution design and implementation.
  • Maintain current knowledge of rapidly evolving machine learning, NLP, LLM, and cloud technologies and identify appropriate opportunities for adoption.
  • Document solution approaches, technical decisions, model considerations, and implementation practices to support maintainability and knowledge sharing.
  • Perform other duties as assigned and adhere to the Code of Conduct and Mission and Value Statement.
Education & Experience:
  • Bachelor's degree in Computer Science Required.
  • Master's degree Preferred.
  • 8+ years of experience as a Data Engineer, NLP/ML Engineer, or similar role, with experience developing and integrating machine learning models and pre-trained APIs in cloud platforms.
  • Equivalent combination of education and/or relevant experience may be considered where appropriate.
Licenses, Certification & Training Requirements: N/A Knowledge, Skills, Abilities, Behaviors: Must Have Skills:
  • Advanced experience designing and developing machine learning and NLP solutions in cloud environments.
  • Deep understanding of NLP techniques, text representation, semantic extraction, statistics, and classification algorithms.
  • Knowledge and expertise in Python and SQL.
  • Experience with machine learning frameworks and APIs.
  • Experience with Google Cloud data and ML technologies, including Vertex AI, LLMs, and Document AI.
  • Experience integrating data platforms and source systems through APIs.
  • Experience training, evaluating, and refining machine learning models using statistical analysis and experimentation.
  • Ability to evaluate technical solutions across cost, scalability, long-term functionality, standards, and business value.
  • Strong analytical, problem-solving, communication, and stakeholder collaboration skills.
  • Ability to work effectively across data science, data engineering, clinical, and business teams.
Nice to Have Skills:
  • Experience working in healthcare information technology
  • Experience with large language models (LLMs), generative AI, or advanced NLP use cases
  • Experience with clinical, coding, or revenue cycle data and workflows
Knowledge, Skills, Abilities and Behaviors:
  • Demonstrates strong technical judgment and the ability to translate complex business needs into practical machine learning solutions.
  • Communicates complex analytical and technical concepts clearly to technical and non-technical audiences.
  • Builds collaborative relationships with internal and external stakeholders and works effectively across cross-functional teams.
  • Provides technical guidance, coaching, and knowledge sharing to strengthen team capabilities.
  • Demonstrates curiosity, innovation, and continuous learning in rapidly evolving machine learning and cloud technologies.
  • Balances solution quality, scalability, maintainability, cost, and organizational standards when making recommendations.
  • Works independently on complex initiatives while maintaining accountability, transparency, and alignment with business objectives.

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