Neuroimaging AI/ML Scientist — Real-Time Interventions

563d Siemens Medical Solutions USA, Inc.; United States; On-site; USD 133,000 - 182,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) retirement plan

Life insurance

Long-term disability insurance

Paid parking/public transportation

Paid time off

Paid sick and safe time

Job summary

Siemens Healthineers is seeking an AI/ML Scientist in Princeton, NJ to develop real-time algorithms for image-guided neurointerventions. You will work with clinical collaborators, imaging scientists, and product teams to translate interventional needs into robust AI solutions covering model development, validation, and deployment in a regulated medical device setting.

The role focuses on fast, accurate AI for interventional workflows, with emphasis on real-time performance and integration with

Qualifications

• MS or PhD in Computer Science, EE, BME, Robotics or related field.
• 2–5 years of AI/ML development experience.
• Hands-on Python, PyTorch or TensorFlow.
• Experience developing/validating ML models for medical imaging.
• Strong problem-solving and ability to explain concepts to technical/clinical audiences.

Responsibilities

• Develop AI algorithms for real-time detection and tracking in fluoroscopy/angiography.
• Develop 2D/3D fusion and registration for intra-procedural views.
• Build foundation models and efficient deployments for real-time latency.
• Create interventional digital twins and simulators for navigation.
• Translate clinical requirements into data, annotations, and model specs.
• Validate algorithms with accuracy, robustness, and latency analyses.

Skills

Python

PyTorch

TensorFlow

Medical imaging

Education

MS or PhD in related field

Tools

TensorRT

ONNX

Job description

Siemens Healthineers is seeking an AI/ML Scientist in Princeton, NJ to develop real-time algorithms for image-guided neurointerventions. You will work with clinical collaborators, imaging scientists, and product teams to translate interventional needs into robust AI solutions covering model development, validation, and deployment in a regulated medical device setting.

The role focuses on fast, accurate AI for interventional workflows, with emphasis on real-time performance and integration with