Principal AI/ML Engineer – Medical Devices

Murata Manufacturing Co., Ltd.; Saint Paul (MN); Hybrid; USD 141,000 - 160,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) employer match

Hybrid work schedule

Tuition reimbursement

Job summary

Murata Manufacturing Co., Ltd. is seeking a Principal Engineer specializing in AI and ML to lead scalable AI platforms and ML pipelines for medical devices. The role blends technical leadership with hands-on model development, regulatory awareness, and collaboration with product, clinical, and QA teams.

You will drive architecture reviews, evaluate new AI technologies, and ensure robust, compliant deployments from research to production across hybrid work arrangements.

Qualifications

• Ph.D. with 7+ years or Master’s degree with 15+ years of relevant industry experience.
• Experience developing deep learning models for biomedical data (images, signals).
• Experience with MLOps: experiment tracking, CI/CD, pipelines, monitoring.

Responsibilities

• Lead architecture and design of scalable AI platforms and ML systems.
• Provide technical leadership and mentorship to AI/ML engineers.
• Collaborate with teams to define AI/ML strategy and roadmaps.
• Develop and optimize ML models for biomedical data and diagnostic support.
• Ensure regulatory compliance and reproducibility across pipelines.

Skills

Deep learning model development

MLOps practices

Python

Regulatory compliance awareness

Cross-functional collaboration

Education

Ph.D. in related field

M.S. with extensive industry experience

Tools

AWS

Azure

Docker

Kubernetes

ONNX

TensorRT

MATLAB

Linux

Python

Job description

Murata Manufacturing Co., Ltd. is seeking a Principal Engineer specializing in AI and ML to lead scalable AI platforms and ML pipelines for medical devices. The role blends technical leadership with hands-on model development, regulatory awareness, and collaboration with product, clinical, and QA teams.

You will drive architecture reviews, evaluate new AI technologies, and ensure robust, compliant deployments from research to production across hybrid work arrangements.