Deep Learning Engineer

Delft Imaging Systems is a leading innovative medical imaging solutions and healthcare technologies provider. Headquartered in 's-Hertogenbosch, the Netherlands, we have built a strong reputation for our cutting-edge products and services that contribute to diagnosing various diseases, particularly in resource-limited settings. Our expertise lies in radiology, where we have developed an array of advanced digital X-ray systems that offer reliable and affordable diagnostic capabilities.

Additionally, we provide artificial intelligence software and mobile clinics for various applications, from X-ray clinics to gynaecology clinics. Operating in over 85 countries, we actively collaborate with governments, non-profit organizations, healthcare institutions, and United Nations agencies to implement sustainable screening programs and improve healthcare worldwide.

Role

In this role at Delft AI, you will focus on cutting edge medical imaging applications that directly impact global health. As part of our Xray team you will contribute to the design and implementation of learning algorithms and be involved in the data engineering, modeling and deployment phases of projects. Your work directly contributes to early disease detection in underserved regions

You will be part of our in-house AI development team, collaborating with stakeholders such as software engineers, research institutions, AI professionals, and potential clients.

Responsibilities 

• Design, develop, and optimize deep learning models for medical image analysis (e.g. X-ray classification, segmentation, and detection tasks)
• Collaborate with software engineers to integrate and deploy models into production environments
• Prepare and process data, including data cleaning, annotation, and pipeline development
• Contribute to our long-term strategic technology roadmap 
• Translate clinical and customer needs into technical solutions in collaboration with medical experts and stakeholders
• Stay up to date with advancements in medical imaging and deep learning, and proactively apply relevant innovations
• Validate and evaluate model performance using clinically relevant metrics and datasets
• Work with diverse, real-world datasets, including data from low-resource environments

Educational background and skills

• Bachelor’s- or master's degree in artificial intelligence, computer science, biomedical engineering or equivalent
• Minimum 2 years of work experience in a related field
• Fluency in English (Dutch optional), in writing and speaking is a must
• Experience in deep learning/machine learning, preferably in the field of computer vision
• Experience in scientific programming (Python and C++ are mandatory)
• Proficiency in deep learning frameworks, PyTorch or TensorFlow.
• Experience with model deployment and optimization (e.g. Docker, C++ inference pipelines, or similar production environments)
• Work accurately and independently, eager to learn and a results-oriented mindset 

Why us?

The opportunity to work in an international, multi-cultural and ambitious team with more than 20 different nationalities. We offer a dynamic work environment in which everyone is encouraged to learn, grow and take ownership. Delft is growing rapidly and with that we foster innovation and personal growth. We encourage following trainings and courses which fit your and the company’s ambition.

What we offer you

• Have a direct positive impact on global healthcare
• 25 vacation days and 1 diversity day
• An excellent pension schema, completely paid for by Delft
• Office in a historical building in Den Bosch
• Flexibility, ownership, autonomy and freedom
• Multiple team outings per year and regular informal get togethers

Do you recognize yourself in the above profile? We would love to schedule an introductory meeting! Send your CV and mandatory motivation letter to [email protected]

Diversity & Inclusion

At Delft Imaging, we reflect the diverse world we serve. We value equity and inclusion, as our team’s multicultural experiences fuel creativity and broaden perspectives. Together, our inclusivity embodies our vision of global health equity.

We welcome qualified applicants of all backgrounds, especially those from diverse and underrepresented ethnicities and groups.