Senior Software Engineer - Machine Learning & Artificial Intelligence; ML & AI

Company Overview

One of the nation’s largest and most respected providers of hospital and healthcare services, Universal Health Services, Inc. (NYSE: UHS) has built an impressive record of achievement and performance. Growing steadily since its inception, UHS is a Fortune 300 corporation with annual revenues of $15.8 billion in 2024. It has been recognized by Fortune as one of the World’s Most Admired Companies and listed by Forbes among America’s Largest Public Companies.

Headquartered in King of Prussia, PA, UHS has approximately 99,000 employees and continues to grow through its subsidiaries, operating acute care hospitals, behavioral health facilities, outpatient facilities, ambulatory care access points, an insurance offer, a physician network and related services across the U.S., D.C., Puerto Rico and the United Kingdom.

The Corporate Information Services Department is seeking a dynamic and talented Sr. Software Engineer – Machine Learning and Artificial Intelligence. This role plays a crucial part in developing AI‑driven solutions that enhance patient care, streamline operations and improve clinical decision‑making. The engineer collaborates with data scientists, clinicians and IT teams to design, implement and optimize AI models that integrate seamlessly into healthcare workflows.

Development and Design

• Design, train and deploy predictive analytics models for disease detection, patient risk assessment and personalized treatment recommendations.
• Develop computer vision algorithms for medical imaging analysis to assist diagnoses and anomaly detection.
• Implement natural language processing models for extracting insights from clinical notes, EHRs and medical literature.
• Architect and develop scalable AI‑driven applications that integrate with healthcare systems.
• Ensure data governance, compliance (HIPAA, GDPR) and security best practices.
• Optimize AI models for real‑time processing and efficient deployment in cloud or on‑premise environments.
• Design and maintain data pipelines for structured and unstructured healthcare data.
• Ensure data quality, preprocessing and feature engineering for AI model training.
• Work with big data technologies to manage large‑scale healthcare datasets.
• Implement robust security measures to protect patient data and prevent unauthorized access.
• Develop explainable AI models to enhance transparency and trust in AI‑driven healthcare decisions.
• Collaborate closely with clinicians, researchers and administrators to define solutions that improve patient outcomes.
• Communicate AI insights effectively to non‑technical stakeholders, ensuring alignment with healthcare objectives.

Maintenance and Support

• Establish monitoring tools to track AI model performance and reliability.
• Provide technical support for AI‑driven healthcare applications, troubleshooting issues and optimizing performance.
• Implement model retraining strategies to adapt solutions to evolving healthcare data and requirements.
• Ensure long‑term sustainability of AI models through version control, documentation and stakeholder feedback.
• Provide technical leadership, mentoring junior engineers and guiding AI strategy within the organization.

Position Requirements

• Bachelor’s or Master’s degree in Computer Science, AI or a related field.
• 5+ years of experience in ML and AI development with a strong focus on healthcare interoperability and platform architecture.

Machine Learning & AI Expertise

• Strong proficiency in Python, Tensor Flow, PyTorch and other ML frameworks.
• Experience with NLP and computer vision for healthcare applications.
• Knowledge of reinforcement learning and large language models (LLMs).
• Familiarity with AI observability and experiment tools such as MLflow.

Platform Architecture & Scalability

• Expertise in microservices architecture, ensuring modular and scalable AI solutions.
• Proficiency in containerization (Docker, Kubernetes) for efficient deployment.
• Experience with cloud platforms (AWS, Azure, GCP) for scalable AI integration.
• Strong understanding of high‑performance computing for large‑scale healthcare data processing.
• Ability to design interoperable systems that integrate…