AI Engineer

About the position

The AI Engineer will play a critical role in designing, developing, deploying, and maintaining artificial intelligence solutions to enhance clinical decision-making, operational efficiency, and patient engagement in a healthcare environment. This position is part of a collaborative team within an AI Center of Excellence, working alongside data scientists, software engineers, clinicians, and IT professionals to deliver impactful AI-driven tools and systems.

Responsibilities

• Design, develop, and implement AI models and algorithms to address healthcare challenges, such as improving clinical decision support, streamlining workflows, and enhancing patient experiences.
• Manage the full AI model lifecycle, including data preparation, model training, testing, deployment, and ongoing maintenance.
• Collaborate with cross-functional teams, including clinicians and IT staff, to ensure AI solutions meet clinical needs and integrate seamlessly into existing healthcare systems.
• Optimize AI models for performance, scalability, and reliability within a healthcare setting.
• Stay current with advancements in AI technologies and healthcare industry trends to propose innovative solutions.
• Ensure compliance with healthcare regulations and data privacy standards throughout the development process.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• Proven experience in developing and deploying AI/ML models, preferably in a healthcare or clinical environment.
• Proficiency in programming languages such as Python, R, or Java, and familiarity with AI frameworks (e.g., TensorFlow, PyTorch).
• Strong understanding of data processing, feature engineering, and model evaluation techniques.
• Experience working with healthcare data (e.g., EHR systems, medical imaging) is a plus.
• Excellent problem-solving skills and ability to work collaboratively in a multidisciplinary team.

Nice-to-haves

• Knowledge of healthcare IT systems and standards (e.g., HL7, FHIR) is preferred but not required.