AI Engineer - Clinical Communication & Workflow Systems

- Develop and deploy AI/ML models to enhance clinical workflows, including call routing, prioritization, escalation, and automation

- Design predictive and analytical models to support staff allocation optimization, alarm fatigue reduction, and patient response prioritization

- Build and integrate AI capabilities into enterprise data and analytics platforms, leveraging aggregated workflow and clinical system data

- Integrate AI capabilities within Rauland's interoperability ecosystem, including nurse call systems, medical devices, and EHR platforms

- Develop intelligent services for event correlation, context-aware alerting, and workflow optimization across connected systems

- Design and implement scalable AI deployment pipelines, including model lifecycle management, monitoring, and drift detection

- Ensure secure and compliant handling of healthcare data aligned with regulatory and hospital requirements

- Collaborate cross-functionally with Software Engineering, Product Management, Clinical teams, and field organizations to translate prototypes into production-ready features

- Contribute to product roadmap initiatives focused on AI-enabled workflow automation and next-generation clinical communication platforms

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field or an equivalent combination of education and relevant experience

- 5+ years of experience in machine learning, data engineering, or AI solution development

- Strong proficiency in Python, SQL, and modern machine learning frameworks (e.g., TensorFlow, PyTorch)

- Experience working with real-time systems, time-series data, or event-driven architectures

- Experience integrating systems through APIs and distributed architectures

- Strong understanding of software engineering best practices, including testing, scalability, and performance optimization

- Demonstrated ability and willingness to use AI tools to improve productivity, decision-making, work quality, and to reduce costs. The successful candidate must be able to identify appropriate AI use cases and critically evaluate AI-generated outputs.

- Experience in healthcare IT systems, clinical workflows, or regulated environments

- Familiarity with interoperability standards such as HL7, FHIR, or similar healthcare protocols

- Experience with cloud-based analytics platforms and hybrid or on-prem deployments

- Exposure to MLOps practices, model deployment pipelines, and lifecycle management

- Understanding of explainable AI and model governance in regulated domains

At Rauland, a division of AMETEK, we're redefining how communication technology supports care and safety in the moments that matter most. From advancing clinical communication in hospitals to enabling critical response systems in schools, our solutions make a real-world impact every day. As part of AMETEK's Measurement, Communications & Technologies division, we offer the best of both worlds - cutting-edge innovation and the backing of a global leader.

Join us in building technology that truly makes a difference. Visit www.rauland.com .