Employee breakdown
AI
40%
Engineering
35%
Operations
25%
Artificial Intelligence / Machine Learning, Health, SocialTech / GreenTech
Paris, Montreal, Munich
Milvue's technical unit of 20 engineers is split into three teams :
The AI team specializes in algorithm development, software design, training wizardry and data management. They use deep learning tools to create models that enhance medical image interpretation and collaborate with medical professionals to ensure real-world applicability. Their goal is to revolutionize healthcare and improve patient outcomes.
The Engineering team integrates advanced AI algorithms into reliable software solutions for medical imaging. They handle software architecture, system design, and deployment while ensuring seamless integration with medical workflows and maintaining software infrastructure.
The Operations team deploys AI-driven imaging software, trains users, and provides support. They collaborate with clients and partners for smooth implementation and integration with systems like PACS. By working with the AI and Engineering teams, they contribute to the ongoing improvement of healthcare and patient outcomes.
AI
40%
Engineering
35%
Operations
25%
Daily Neural Network Trainings
The versatile and powerful programming language driving our backend infrastructure, enabling efficient development and seamless integration with AI frameworks.
A modern, high-performance web framework that streamlines the creation of robust and scalable APIs for our medical imaging software solutions.
A user-friendly deep learning library built on top of TensorFlow, simplifying the development and training of AI models in medical imaging for improved diagnostic accuracy and speed.
While each team's approach may differ, they all share key values: teamwork, code quality, and continuous improvement. They engage in activities such as reviewing workflows, sprint meetings, open discussions, and evaluating contributions. Teams adopt methodologies that best suit their needs, such as Agile or working in squads, always aiming to deliver top-notch software and services through efficient collaboration.
Emphasizing open communication and knowledge exchange, team members can effectively share ideas and provide feedback. Regular team rituals, like weekly meetings and pairing sessions, foster a supportive and productive work environment, promoting cooperation and a shared sense of accomplishment.
Our team recently embarked on a demanding technical endeavor focused on extracting 50 crucial measurements from X-ray images with the help of AI. By drawing upon our collective knowledge in deep learning and medical imaging, we crafted an extremely precise model that can identify and measure anatomical structures with remarkable accuracy. This innovation not only simplifies diagnostic procedures but also supports treatment planning, ultimately enhancing patient outcomes. The project's success can be attributed to our team's cooperative spirit and forward-thinking approach.
During a recent project, our attention centered on integrating our medical imaging solutions with a DICOMweb platform, placing special emphasis on API development. By harnessing FastAPI, we devised coherent and effective API schemas, facilitating seamless interaction between our software and the DICOMweb platform. The team's proficiency in API development and comprehension of DICOM standards enabled us to construct a compatible solution that effortlessly integrates outputs into clinical workflows, optimizes processes, and safeguards data integrity and security.
For candidates applying to the AI team, the interview process will consist of an initial conversation with a team member, followed by a technical assessment, and finally, a concluding interview with a senior team member. As for software and operations team applicants, the process will involve an introductory call with the team leader, followed by a pair of technical interviews.