AI​/ML Engineer

An AI/ML Engineer in the health IT domain with experience in HL7 data standards is responsible for designing, developing, training, and deploying machine learning and AI solutions tailored to health IT applications. This role involves working closely with adverse events data, including HL7 and other clinical data standards, to build scalable, accurate, and efficient AI models that improve drug safety, signal detection and operational efficiency.

Chickasaw Nation Industries, Inc. serves as a holding company with multiple subsidiaries engaged in several lines of business (Technology, Infrastructure & Engineering, Health, Manufacturing, Public Safety, Consulting, and Transportation) for the federal government and commercial enterprises. A portion of our profits is used to support Chickasaw citizens. We are proud to support the economic development and long‑term viability of the Chickasaw Nation and its people.

CNI offers premium benefits eligible on the first day of hire to full time employees; (Medical - Dental – Vision), Company Life Insurance, Short‑Term and Long‑Term Disability Insurance, 401(K) Immediate Vesting, Professional Development Assistance, Legal Aid Assistance Program, Family Planning / Fertility Assistance, Personal Time Off, and Observance of Federal Holidays.

As a federal contractor, CNI is a drug‑free workplace and adheres to the Federal Controlled Substance Act.

• Must possess appropriate level of certifications for this position as required by the contract.
• Must be able to obtain a customer clearance for access to facilities, equipment and property.
• Strong programming skills in Python, R, or Java with experience in AI/ML frameworks and libraries.
• Deep understanding of machine learning algorithms, statistical models, deep learning, and generative AI techniques.
• Experience working with healthcare data standards, especially HL7 and FHIR, to process and interpret clinical data.
• Familiarity with cloud computing platforms (AWS preferred), containerization, and CI/CD pipelines for AI model deployment.
• Knowledge of healthcare workflows, clinical environments, and regulatory compliance (e.g., HIPAA) is essential.
• Strong analytical, problem‑solving, and communication skills to translate complex AI concepts into clinical applications.
• Experience with NLP, computer vision, or other domain‑specific AI applications in healthcare is a plus.
• Prior work in healthcare or health IT companies, handling large‑scale healthcare datasets is preferred.
• Hands‑on experience with GenAI models, Lang Chain, Vector
  
  DBs, and RAG techniques for advanced AI solutions is preferred.
• Leadership or mentorship roles in AI/ML projects within healthcare settings is preferred.

Essential duties and responsibilities include the following. Other duties may be assigned.

• Builds, trains, validates, and deploys machine learning models to solve healthcare‑specific problems such as predictive analytics, anomaly detection, clinical decision support, and natural language processing on medical data.
• Develops AI/ML solutions that integrate HL7 and other healthcare interoperability standards to ensure seamless data exchange and compliance with healthcare regulations.
• Collaborates with clinicians, data engineers, product managers, and compliance teams to align AI solutions with clinical workflows and regulatory requirements such as HIPAA.
• Implements and optimizes models using Python, R, Java, or other relevant programming languages and frameworks (e.g., PyTorch, Tensor Flow, scikit‑learn).
• Fine‑tunes large language models (LLMs) and leverages generative AI techniques, including Retrieval‑Augmented Generation (RAG) and agentic frameworks, to enhance healthcare AI applications.
• Conducts rigorous evaluation of AI models using appropriate metrics and continuously monitors and improves model performance in production environments.
• Designs and maintains AI/ML pipelines and infrastructure, often utilizing cloud platforms such as AWS, Azure, or Google Cloud for scalable model training and deployment.
• Ensures ethical AI use and compliance with healthcare regulations, including data privacy and security…