Senior Healthcare AI Engineer - Remote - Scalable Models

Neurex AI; United States; Remote; USD 150,000 - 230,000; Full time

Benefits offered by this job

Remote work

Job summary

Neurex AI is building and deploying applied AI systems for healthcare, spanning models, integrations, and scalable inference. The role covers the full path from exploring a solution to operating it in production.

You will design AI features for clinical workflows, develop ML models, and build scalable serving pipelines. Collaboration with product, engineering, and clinical experts is essential for delivering validated outputs.

Qualifications

• Five+ years of experience building and deploying machine-learning systems in production.
• Strong foundations in machine learning and software engineering.
• Experience with Python and PyTorch or TensorFlow.
• Experience with cloud infrastructure.
• Ability to work through ambiguous, real-world problems with ownership and execution focus.
• Clear communication and high standards for delivered work.

Responsibilities

• Design and deploy AI features for clinical and revenue-cycle workflows.
• Develop and improve machine-learning models for healthcare-specific applications.
• Build scalable model-serving and inference pipelines.
• Own AI features through research, implementation, and production deployment.
• Partner with product, engineering, customer teams, and clinical experts to deliver solutions and validate outputs.
• Contribute to systems for clinical documentation, coding, denials management, and operator or clinician copilots.

Skills

ML engineering

Python

Cloud infrastructure

Software engineering

Ownership

Communication

Tools

PyTorch

TensorFlow

Job description

Neurex AI is building and deploying applied AI systems for healthcare, spanning models, integrations, and scalable inference. The role covers the full path from exploring a solution to operating it in production.

You will design AI features for clinical workflows, develop ML models, and build scalable serving pipelines. Collaboration with product, engineering, and clinical experts is essential for delivering validated outputs.