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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.
Job Responsibility:
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, TensorFlow, scikit-learn)
Fine-tunes large language models (LLMs) and leverage 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 monitor and improve 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 standards
Provides mentorship and technical guidance to junior engineers and contribute to research and development efforts in healthcare AI
Requirements:
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
Nice to have:
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, LangChain, VectorDBs, and RAG techniques for advanced AI solutions is preferred
Leadership or mentorship roles in AI/ML projects within healthcare settings is preferred