Experienced AI Engineer Clinical Imaging Software Suite

Job Title

Experienced AI Engineer Clinical Imaging Software Suite

Job Description

As an Experienced AI Engineer, you will join a high-performing team within the Image Guided Therapy Devices (IGT-D) Software R&D group in Best, Netherlands. In this role, you’ll work on cutting-edge AI/ML features for our Intravascular Ultrasound (IVUS) Clinical Imaging Software Suite. You will be responsible for developing and deploying deep-learning models in customer-facing products that significantly enhance clinical workflows. From concept to commercialization, your work will comply with all medical regulatory standards to deliver meaningful healthcare solutions.

We are looking for AI/ML engineers with proven experience in bringing AI algorithms to market and maintaining them in live commercial products within the healthcare industry.

Your Role:

• AI Model Development & Deployment:
  Design, train, and optimize machine learning models to support clinical decision-making, ensuring compliance with medical regulations. Focus on deploying AI models in the field and maintaining them with real-world data collection and re-tuning.

• Implementation & Monitoring:
  Implement AI models in production software using Python (C++ or C# knowledge is a plus). Ensure compliance with medical device standards and regulatory requirements for data usage. Monitor deployed models, retrain when needed, and maintain safety and reliability.

• Collaboration & Documentation:
  Partner with data scientists to refine models using clinical data. Create thorough documentation for development, deployment, and updates to support audits and regulatory reviews.

• Testing & Validation:
  Validate models in clinical environments, ensuring their real-world performance meets safety and efficacy standards. Investigate and resolve performance inconsistencies with a focus on patient outcomes.

• Regulatory Compliance & Risk Management:
  Apply expertise in medical software regulations (FDA, MDR, ISO 13485) to ensure data usage and AI implementations align with compliance requirements.

• Ethical & Practical Considerations:
  Protect patient privacy (e.g., GDPR, HIPAA) and address biases to deliver equitable, ethical AI-driven solutions.

You’re the Right Fit If:

• You have a Master’s degree in Computer Science, Computer Engineering, Data Science, or a related discipline.

• You bring 6+ years of experience as a Machine Learning Engineer or in a similar role.

• You have successfully deployed AI-powered medical products in real-world commercial settings.

• You are skilled in deep learning frameworks (e.g., PyTorch, TensorFlow) and architectures like UNet or ResUNet.

• You preferably understand regulatory compliance (e.g., IEC 62304, ISO 13485) and its role in deploying AI solutions.

• You have experience collecting data and tuning AI models for field deployment while adhering to regulatory frameworks.

• You’re proficient with common tools like Azure DevOps/Jira, Git, build/DevOps tools such as CMAKE, GitHub/Jenkins and artifact managers such as Artifactory.

• You have experience working with Phyton and preferably C++ or C#

• You are committed to ensuring patient safety and delivering compliant, effective AI-driven healthcare solutions.

How we work together

We believe that we are better together than apart. For our office-based teams like this one, it means working in-person at least 3 days per week.
 

About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.

• Learn more about our business.

• Discover our rich and exciting history.

• Learn more about our purpose.

If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our commitment to diversity and inclusion here.

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